{"id":"d35c12e6-ac28-44c8-8f2f-f2bf184f7e22","entityType":"agent","slug":"clawhub-medstatstar-statsoft-cli","name":"statsoft-cli","canonicalUrl":"https://www.xpersona.co/agent/clawhub-medstatstar-statsoft-cli","canonicalPath":"/agent/clawhub-medstatstar-statsoft-cli","generatedAt":"2026-10-09T19:14:30.145Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T11:12:52.176Z","emptyReason":null},"description":"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation. Skill: statsoft-cli Owner: medstatstar Summary: 跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation. Tags: Initial Release:1.2.0, latest:2.8.2 Version history:","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 2.8K downloads reported by the source. 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Core value: activating historical code assets for AI workflow automation.\n\nTags: Initial Release:1.2.0, latest:2.8.2\n\nVersion history:\n\nv2.8.2 | 2026-08-02T12:14:42.418Z | user\n\nR1-R10 hardening (B1-B16) + ClawHub security-audit remediation; 48/48 tests pass.\n\nv2.7.1 | 2026-07-22T04:42:17.904Z | user\n\nFix Minitab GUI-only classification; force *.sh eol=lf; fix SkillHub README links to absolute GitHub URLs\n\nv2.7.0 | 2026-07-22T03:18:21.521Z | user\n\nImproved Minitab support: added Windows detection script (setup_minitab.ps1), scan_all.ps1 detection block, fixed ADDITIONAL_SOFTWARE routing (mtb.exe /?) and command-examples (mtb.exe /run) and config-templates; fixed write_config.py path+BOM bugs affecting all windows-only setup scripts; bilingual compliance per ct-base (stripped residual bilingual headings, added cn_name, added English-only AGENTS.md). Bumped to 2.7.0.\n\nv2.6.23 | 2026-07-19T03:47:47.321Z | user\n\nLocale auto-switch alignment; bilingual doc headings; cross-reference dead-link fixes; 2 bug fixes\n\nv2.6.18 | 2026-07-18T02:32:33.319Z | user\n\nFix TP4 HIGH (description enumerates 4 behavior classes: host inventory, third-party binary execution, file creation, untrusted native code) + AST4 x2 MEDIUM (dedicated STATSOFT_CMDSTAN_RUN gate + warnings)\n\nv2.6.17 | 2026-07-14T07:54:07.938Z | user\n\nClear residual TP4 HIGH + 2xSDI-4: REVEAL gates now control config writes; SKILL.md contradiction fixed\n\nv2.6.16 | 2026-07-13T09:00:56.963Z | user\n\nv2.6.16: TP4 root fix — description-behavior alignment. Description now explicitly discloses ALL file operations: persistent config.json + .bak backups, ephemeral temp dirs, user-directed SPSS .spj/.spv, CmdStan build artifacts. Trust Boundary section rewritten. Gretl/SPSS: variable quoting fix for --version calls.\n\nv2.6.15 | 2026-07-12T10:17:22.781Z | user\n\nv2.6.15: Bilingual restructure (EN-first, CN-second). SKILL.md reduced from 20.6 KB to 9.2 KB. All sections now have bilingual headers (EN/CN). Detailed workflow moved to references/workflow.md. Full platform matrix moved to references/platform-support.md. Default-Deny Gates table now 4-column bilingual. All scripts already have LANG_ZH() auto-switch.\n\nv2.6.14 | 2026-07-12T09:31:08.957Z | user\n\nv2.6.14: Removes accidental maintenance utility from shipped package, fixes Mathematica/H2O/GenStat/OxMetrics/Rattle/Limdep/Q_MRKS/SHAZAM gates, and resolves spsj cleanup regression. All gate implementations now aligned with documented default-deny model.\n\nv2.6.13 | 2026-07-12T09:16:41.500Z | user\n\nv2.6.13: clears all 15 remaining audit findings (1H/13M/1L): Mathematica/H2O HIGH fixes, Gretl malformed structure, JAGS/OpenBUGS/SHAZAM inline-shell leaks, Orange/Rattle path leaks, NCSS data-at-rest, SPSS scan s&s reveal gate, H2O examples warning, 28 sh files syntax-corrected + 9 function-body definitions moved to top-level. Complete 4-gate system (AUTO_WRITE/CONFIRM/REVEAL/VERIFY) covers all 45+ scripts.\n\nv2.6.12 | 2026-07-12T08:08:39.337Z | user\n\nv2.6.12 — critical audit fixes: single-path enforcement + TP4 alignment. write_config.py enforces single canonical config.json path (eliminates arbitrary file write HIGH finding). SPSS version command requires STATSOFT_VERIFY=1. SPSS top-level path prints gated behind STATSOFT_REVEAL=1. SKILL.md adds disclosure/verification gate section for exact description-code alignment (TP4 root fix).\n\nv2.6.11 | 2026-07-12T03:47:02.979Z | user\n\nv2.6.11: systematic root-class remediation — StatTransfer config.json path changed from hardcoded $HOME/.workbuddy to script-relative ROOT_DIR/../config.json + manual-path STATSOFT_VERIFY gate with executable check; Stata verify_stata before save_config + unified validation; scan_all uniform reveal opt-in (boolean-only without consent) + remove python --version execution; CmdStan full-path make target + matching run binary + truncated output; SKILL.md TP4 disclosure of single config path / scan_all gating / STATSOFT_VERIFY\n\nv2.6.10 | 2026-07-12T03:01:30.037Z | user\n\nv2.6.10: systematic root-class remediation of SkillSpector findings — TP4 SKILL.md disclosure of .spj/.spv artifacts + manual-path validation; STATSOFT_VERIFY=1 opt-in gate for version checks (Gretl/JAGS/SHAZAM/Julia/R/StatTransfer/SPSS-setup); remove persistent-env-var guidance (SPSS/GraphPad/JMP); derive version from install path (Origin/NCSS); Microfit config read-after-opt-in; SAS/SPSS data-info behavior alignment; CmdStan artifact confinement; SPSS runner in-band disclosure\n\nv2.6.9 | 2026-07-12T01:35:31.403Z | user\n\nv2.6.9: resolve 13 SkillSpector findings — TP4/RA2 SCOPE disclosure in SKILL.md (host-wide inventory, 3rd-party exec during verification, install flows, config.json persistence confined to skill dir), SAS temp dir cleanup, Stata manual-path executable validation, AMOS helper --consent/--no-write gate, SPSS version default-deny gate, StatTransfer run/batch auth gate + dry-run, example_workflow/completion-prompts doc alignment\n\nv2.6.8 | 2026-07-12T01:06:59.809Z | user\n\nv2.6.8: resolve 25 SkillSpector findings — remove environment_variable_modification capability, remove Prism prismWriter .pzfx rec, remove trust-and-safety MEMORY.md row, remove Modeler remote server-run example, declare NCSS/Origin in manifest, centralized --consent gate replacing self-set STATSOFT_AUTO_WRITE in 10 setup scripts\n\nv2.6.7 | 2026-07-11T14:56:07.489Z | user\n\nv2.6.7: resolve 16 SkillSpector findings — data-info default-deny auth gate + temp cleanup (SAS), cmdstan output arg sanitization (OH1), removed Prism .pzfx write example, SPSS output_dir path containment, ephemeral R pkg-scan temp dir, scan_all -Target scoping + consent, modeler server-run removal (local-only), per-step workflow invocation, consistent persistence-model docs (no MEMORY.md/env writes)\n\nv2.6.6 | 2026-07-11T14:29:01.960Z | user\n\nv2.6.6: temp-file cleanup + default-deny auth gates for SAS/EViews/SPSS data-info, safe log paths, detection-only setup_sas fallback, mktemp verify for stata; repaired 9 broken setup scripts; narrowed triggers\n\nv2.6.5 | 2026-07-11T14:00:56.721Z | user\n\nv2.6.5: default-deny auth gates (SDI-4), no user env-var writes (SDI-1), minimal subprocess env (E2), .spj syntax validation (AST4), stanc output sanitize (OH1), temp-script argv-passing (SQP-2), doc scope trim (TP4/SQP-1/RA2)\n\nv2.6.4 | 2026-07-10T14:26:58.052Z | user\n\nSkillSpector audit fixes: Statistica detection-only + guarded runner, SPSS data-info injection fix, SDI-4 pre-gate dir removal, JMP COM removal, SQP-2 scan consent gates, OH1 CmdStan output sanitize, TP4/RA2/SQP-1 trust boundary\n\nv2.6.3 | 2026-07-10T14:04:38.922Z | user\n\nv2.6.3: fail-closed gates for env-var writers + runner execution auth (SDI-1).\n\nv2.6.2 | 2026-07-10T13:25:47.094Z | user\n\nv2.6.2: explicit inline opt-in gate in every write_config.py caller (SDI-1 root fix), removed misleading 'Updating config' messages (SDI-4), aligned GUI-only/JMP/Mathematica docs with manifest (SDI-1/SDI-2/TP4).\n\nv2.6.1 | 2026-07-10T13:00:14.607Z | user\n\nv2.6.1: centralized fail-closed write gate (write_config.py), removed ungated cat> create branches in R/SAS/Stata, R package cache opt-in, doc/behavior consistency fixes.\n\nv2.6.0 | 2026-07-10T11:47:22.533Z | user\n\nv2.6.0: SkillSpector audit remediation - fail-closed config writes (default detection-only; persist via STATSOFT_AUTO_WRITE=1 or STATSOFT_CONFIRM=1); GUI-only boundary cleanup (AMOS/GraphPad/JASP/jamovi); GraphPad wrapper no longer executes prism.exe.\n\nv2.5.0 | 2026-07-10T10:19:21.432Z | user\n\nSecurity & correctness hardening (v2.5.0): A) timestamped backup + opt-in confirm + atomic write for 22 config writers; B) R package install requires explicit user confirmation; C) removed non-existent GraphPad CLI example; D) SPSS run gate uses opt-in STATSOFT_CONFIRM; E) narrow drive scan to C:/D: only; F) tightened triggers + activation boundary; G) h2o network-listener warning; H) pinned CmdStan to v2.37.0; I) respect user language; J) clarified GUI-only scope. Also fixed pre-existing parse-breaking stray quotes in setup_spss.ps1.\n\nv2.4.0 | 2026-07-10T09:02:31.077Z | user\n\nSecurity audit remediation (2.3.0->2.4.0): tightened description scope (Tp4); marked GUI-only software (AMOS/GraphPad Prism/JASP/jamovi) in platform table + READMEs; clarified format conversion is via Stat/Transfer CLI only; added SETUP-tool framing comments to setup scripts; R installer shows SHA256 + no auto-sudo on Linux; data-info no longer silently installs haven (asks first, skips non-interactive); R package inventory moved to workspace cache; SPSS helper hardened (_run_silent list guard + validate_syntax before Submit); de-single-worded triggers; non-interactive Read-Host fallbacks.\n\nv2.3.0 | 2026-07-10T08:27:56.010Z | auto\n\nstatsoft-cli 2.3.0\n\n- Updated command examples for statistical software in `references/command-examples.md`.\n- Improved completion prompt templates in `references/completion-prompts.md`.\n- Enhanced cross-platform setup scripts for Matlab and R.\n- Updated Windows-only setup script for JMP.\n- Other minor documentation and script adjustments for consistency.\n\nv2.2.0 | 2026-07-10T08:06:13.576Z | auto\n\nstatsoft-cli 2.2.0\n\n- Added explicit capability metadata (e.g., shell execution, env vars, system scanning) in SKILL.md.\n- Updated version to 2.2.0 across metadata.\n- Various documentation updates in SKILL.md and related files.\n- Improved clarification of platform support and workflow steps in documentation.\n- No user-facing CLI or workflow changes; changes are documentation and metadata only.\n\nv2.1.0 | 2026-07-10T07:13:29.378Z | auto\n\nstatsoft-cli v2.1.0\n\n- Enhanced description and documentation for clarity; now explicitly lists capabilities such as software detection (read-only scanning), batch/silent CLI execution, config backup/confirmation, and environment variable management.\n- Pre-scan confirmation step updated: scan is now explicitly described as read-only and non-destructive before user chooses to scan or manually specify paths.\n- Configuration writes now require explicit user confirmation and include automatic timestamped backup of existing config.json files.\n- Any environment variable modification scripts now require explanation and user consent before proceeding.\n- Expanded and refined trigger phrases for both Chinese and English.\n- Removed outdated skill-card.md file.\n\nv2.0.0 | 2026-07-03T11:56:43.606Z | auto\n\nNo file changes detected for this release.\n\n- Version bump to 2.0.0 with no source or documentation changes.\n- All functionality and documentation remain unchanged from the previous release.\n\nv1.4.0 | 2026-07-01T03:26:56.237Z | auto\n\nstatsoft-cli 1.4.0\n\n- Updated SKILL.md metadata version to 1.4.0.\n- Documentation updates in README.md, README_zh-CN.md, and SKILL.md.\n- No functional code changes; release is for documentation and metadata/version alignment.\n\nv1.3.0 | 2026-07-01T02:56:52.308Z | auto\n\n**Major update with enhanced documentation, security transparency, and extended support.**\n\n- Complete rewrite and expansion of documentation, highlighting trust & safety considerations and detailing workflow steps.\n- Added detailed sections for risk levels, permissions, and pre-flight checks to improve user safety/awareness.\n- Broadened platform/software support table and clarified core vs. extended software.\n- Introduced in-depth use cases and outlined reference files for advanced configuration and troubleshooting.\n- Integrated new files: LICENSE, detailed READMEs (including Chinese), and reference guides for command examples and version differences.\n- Deprecated/removed older files (e.g., skill-card.md); updated authors and metadata.\n\nv1.0.0 | 2026-06-30T14:14:08.235Z | auto\n\nInitial release.\n\n- Adds cross-platform statistical software CLI integration for WorkBuddy\n- Supports major software (R, Stata, SAS, SPSS, JMP, GraphPad Prism, Gretl, Minitab, Matlab, Julia, EViews, Statistica, Stat/Transfer)\n- Auto-detects platform and hides incompatible software\n- Bilingual support (中文/English)\n- Script routing and workflow for software setup and execution\n- Includes example test files and configuration documentation\n\nv1.2.0 | 2026-06-30T14:11:22.754Z | auto\n\n- Added bilingual (中文/English) platform support and clear trigger phrases for easier access.\n- Expanded software integration; now supports R, Stata, SAS, SPSS, JMP, GraphPad Prism, Gretl, Minitab, Matlab, Julia, EViews, Statistica, and Stat/Transfer.\n- Auto-detects operating system/platform and hides incompatible software options.\n- Introduced detailed step-by-step execution workflow: platform detection, info gathering, mode selection (simple/advanced), script routing, config saving, and summary output.\n- Comprehensive configuration and routing tables for scripts and verification commands included.\n- Documentation updated with test file info, software support matrix, and additional configuration references.\n\nArchive index:\n\nArchive v2.8.2: 86 files, 245370 bytes\n\nFiles: ADDITIONAL_SOFTWARE.md (32487b), ADVANCED_zh-CN.md (3189b), ADVANCED.md (3181b), AGENTS.md (5719b), assets/icon.svg (1601b), CHANGELOG.md (57098b), LICENSE (1105b), README_zh-CN.md (7641b), README.md (7560b), references/command-examples.md (14941b), references/completion-prompts.md (22007b), references/config-templates.md (8918b), references/platform-support.md (1199b), references/trust-and-safety.md (1015b), references/version-specifics.md (14286b), references/workflow.md (1705b), scripts/common/write_config.py (7629b), scripts/cross-platform/_platform-detect.sh (2032b), scripts/cross-platform/CmdStan/setup_cmdstan.sh (4092b), scripts/cross-platform/CmdStan/statsoft-cmdstan.py (11057b), scripts/cross-platform/GenStat/setup_genstat.sh (3675b), scripts/cross-platform/Gretl/setup_gretl.sh (8431b), scripts/cross-platform/H2O/setup_h2o.sh (4169b), scripts/cross-platform/JAGS/setup_jags.sh (3928b), scripts/cross-platform/jamovi/setup_jamovi.sh (3376b), scripts/cross-platform/JASP/setup_jasp.sh (3217b), scripts/cross-platform/Julia/setup_julia.sh (9875b), scripts/cross-platform/KNIME/setup_knime.sh (3159b), scripts/cross-platform/Mathematica/setup_mathematica.sh (7250b), scripts/cross-platform/Matlab/setup_matlab.sh (10532b), scripts/cross-platform/Minitab/setup_minitab.sh (6977b), scripts/cross-platform/Mplus/setup_mplus.sh (2995b), scripts/cross-platform/OpenBUGS/setup_openbugs.sh (3953b), scripts/cross-platform/Orange/setup_orange.sh (4700b), scripts/cross-platform/OxMetrics/setup_oxmetrics.sh (3857b), scripts/cross-platform/PSPP/setup_pspp.sh (3108b), scripts/cross-platform/R/setup_r.sh (16318b), scripts/cross-platform/Rattle/setup_rattle.sh (5604b), scripts/cross-platform/SAS/setup_sas.sh (12696b), scripts/cross-platform/scan/scan_all.sh (8979b), scripts/cross-platform/SHAZAM/setup_shazam.sh (3858b), scripts/cross-platform/Stata/setup_stata.sh (10877b), scripts/cross-platform/StatTransfer/setup_stattransfer.sh (11625b), scripts/cross-platform/Tanagra/setup_tanagra.sh (3653b), scripts/cross-platform/TSP/setup_tsp.sh (3611b), scripts/cross-platform/Weka/setup_weka.sh (3481b), scripts/windows-only/AMOS/setup_amos.ps1 (8941b), scripts/windows-only/AMOS/setup_amos.py (6842b), scripts/windows-only/EViews/setup_eviews.ps1 (4624b), scripts/windows-only/EViews/statsoft-eviews.ps1 (3604b), scripts/windows-only/GraphPad/setup_graphpad.ps1 (8360b), scripts/windows-only/GraphPad/statsoft-graphpad.ps1 (4324b), scripts/windows-only/JMP/setup_jmp.ps1 (7992b), scripts/windows-only/JMP/statsoft-jmp.ps1 (7055b), scripts/windows-only/Limdep/setup_limdep.ps1 (4777b), scripts/windows-only/Mathematica/setup_mathematica.ps1 (6050b), scripts/windows-only/Microfit/setup_microfit.ps1 (4533b), scripts/windows-only/Minitab/setup_minitab.ps1 (6482b), scripts/windows-only/Mplus/setup_mplus.ps1 (4383b), scripts/windows-only/NCSS/setup_ncss.ps1 (4997b), scripts/windows-only/NLOGIT/setup_nlogit.ps1 (4187b), scripts/windows-only/Origin/setup_origin.ps1 (4962b), scripts/windows-only/Q_MRKS/setup_q.ps1 (4917b), scripts/windows-only/scan/scan_all.ps1 (21793b), scripts/windows-only/SHAZAM/setup_shazam.ps1 (4579b), scripts/windows-only/SPSS/_data_info.py (980b), scripts/windows-only/SPSS/_spss_runner.py (1325b), scripts/windows-only/SPSS/run-spss-internal.py (7383b), scripts/windows-only/SPSS/setup_modeler.ps1 (5078b), scripts/windows-only/SPSS/setup_spss.ps1 (17964b), scripts/windows-only/SPSS/spss_helper.py (25798b), scripts/windows-only/SPSS/statsoft-modeler.ps1 (7031b), scripts/windows-only/SPSS/statsoft-spss.ps1 (19574b), scripts/windows-only/Statistica/setup_statistica.ps1 (6888b), scripts/windows-only/Statistica/statsoft-statistica.ps1 (3867b), scripts/windows-only/statsoft-r.ps1 (9159b), scripts/windows-only/statsoft-sas.ps1 (7319b), scripts/windows-only/StatTransfer/statsoft-stattransfer.ps1 (13408b), skill-card.md (3108b), SKILL.md (10949b)\n\nFile v2.8.2:SKILL.md\n\n---\nname: statsoft-cli\nslug: statsoft-cli\ndisplayName: 统计软件接入助手 / Statsoft-CLI\ncn_name: 统计软件接入助手\nversion: \"2.8.2\"\nsummary: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。\"\nlicense: MIT\ndescription: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation.\"\ntriggers:\n - \"SPSS\"\n - \"SPSS Statistics\"\n - \"R命令行\"\n - \"Stata\"\n - \"SAS\"\n - \"统计软件\"\n - \"连接统计软件\"\n - \"statsoft-cli\"\n - \"connect statistical software\"\nrequired_commands: [python, bash, powershell]\nmetadata:\n {\n \"openclaw\": { \"emoji\": \"🛠️\", \"icon\": \"assets/icon.svg\" },\n \"authors\": [\"medstatstar\", \"phoe-zip\"],\n \"contributors\": [\"medstatstar\", \"phoe-zip\"],\n \"version\": \"2.8.2\",\n \"license\": \"MIT\",\n \"tags\": [\"Statistical Software\", \"CLI\", \"R\", \"SPSS\", \"Stata\", \"SAS\", \"Bayesian\", \"Machine Learning\", \"Econometrics\", \"SEM\", \"Data Mining\"],\n \"homepage\": \"https://github.com/medstatstar/statsoft-cli\",\n \"repository\": \"https://github.com/medstatstar/statsoft-cli\"\n }\npermissions:\n scope: \"user-space-only\"\n network: \"off\"\n network_note: \"Offline by default; only CRAN / Anaconda repo access for local dependency install, requires explicit confirmation.\"\n filesystem: \"read-only to its own files; writes only config.json under skill root with explicit opt-in\"\n data: \"no external data transmission\"\n---\n\n## Language\n\nPick the README that matches your language for human-readable, language-specific guides:\n\n- **English guide** → [README.md](https://github.com/medstatstar/statsoft-cli/blob/main/README.md)\n- **中文指南** → [README_zh-CN.md](https://github.com/medstatstar/statsoft-cli/blob/main/README_zh-CN.md)\n\nThis skill responds in the user's current input language (Chinese or English) and auto-detects / switches accordingly. The runtime scripts embed a locale check (`$script:isZH` in PowerShell, `SCRIPT_LANG` in Bash) so all user-facing prompts switch to Chinese on a `zh-*` UI culture and to English otherwise. Code comments and documentation are English-only.\n\nThe SKILL.md body, `references/*.md`, and `ADDITIONAL_SOFTWARE.md` are English-only and agent-facing; runtime command prompts switch to Chinese / English by locale. For end-to-end walkthroughs, examples, and troubleshooting in your language, open the README above.\n\n## Overview\n\nActivates historical code assets locked in statistical software (syntax, scripts, projects) and wires them into AI workflows via automated detection, configuration, and execution.\n\n## Core Functions\n\nCovers 34+ statistical / data-science packages, auto-routed by platform; non-Windows auto-hides incompatible software:\n\n- **Cross-platform (Win / Mac / Linux, CLI)**: R, Stata, SAS, CmdStan, GenStat, Gretl, H2O.ai, JAGS, Julia, KNIME, Mathematica, Matlab, OpenBUGS, Orange, OxMetrics, PSPP, Rattle, SHAZAM, Stat/Transfer, Tanagra, TSP, Weka\n- **Windows + limited cross-platform**: Mplus\n- **Windows-only CLI**: SPSS Statistics, EViews, JMP, LIMDEP, Microfit, NCSS, NLOGIT, Origin, Q(MRKS), SPSS Modeler, Statistica\n- **GUI-only detection + manual launch guide**: AMOS, GraphPad Prism, JASP, jamovi, Minitab (never drive batch via CLI; `mtb.exe /run` opens the Minitab GUI, not headless)\n\nFull platform matrix in `references/platform-support.md`; extended config in `ADDITIONAL_SOFTWARE.md`.\n\n## Router Paths\n\nWhen gate 0 classifies a request as **Simple** (clear tool + action), route straight to the canonical per-tool entry script. These are the 6 primary entry points; the rest are auto-discovered from the platform matrix:\n\n- `scripts/windows-only/SPSS/setup_spss.ps1` — SPSS Statistics (Windows)\n- `scripts/windows-only/statsoft-r.ps1` — R CLI wrapper / data conversion (Windows)\n- `scripts/cross-platform/R/setup_r.sh` — R (cross-platform)\n- `scripts/cross-platform/Stata/setup_stata.sh` — Stata (cross-platform)\n- `scripts/windows-only/statsoft-sas.ps1` — SAS (Windows)\n- `scripts/cross-platform/SAS/setup_sas.sh` — SAS (cross-platform)\n\n## Clarification Gate (gate 0) — friendly menu policy\n\nPer ct-base §13 (the same pattern ct-advisor implements as its gate 0), this skill **triages the user's first message before opening any menu** and **defaults to the friendliest path**. The interactive menus (scan-confirmation, config-mode selection) are only shown when step-by-step confirmation genuinely helps — never forced onto a simple request.\n\nClassify the first message into one of three paths:\n\n- **Simple** — specific, single-intent, answerable directly (e.g. \"Connect SPSS 26\", \"Convert data.sav to data.dta\", \"Run my Stata do-file batch\"). → Detect / act in one pass. **Do NOT pop the scan or config menu.** If the tool and target are clear, route straight to detection / configuration (detect-only by default) and report; optionally offer a deeper step (\"want me to also scan for the rest?\") rather than demanding a choice.\n- **Complex** — multi-decision or \"set up everything / I'm not sure what's installed\" (Example 4 in the README). → Present the **routing menu** (auto-scan vs specify-paths) and confirm step by step. Only open the full menu when step-by-step confirmation genuinely helps.\n- **Vague** — need unclear / user undecided (Example 5, \"I want to use statistical software but don't know where to start\"). → Enter **grill-me clarify mode**: ask 1–3 conclusion-changing questions per round (which tools are installed? what do you want to do — run old scripts / convert data / build new analysis? headless or GUI?), branch-by-branch, until the right tool is locked — never dump the 34-tool list or pick for the user.\n\n**Default to the friendliest path**: when in doubt between simple and complex, give a short direct detection + an optional deeper-menu offer instead of forcing a menu. When the user's first message already names a clear target (a specific tool + action), **skip the menu entirely** and go straight to detection / configuration.\n\n> The clarification strings themselves follow the locale switch (`$script:isZH` / `SCRIPT_LANG`), so menus and probes render in Chinese on a `zh-*` system and English otherwise — consistent with ct-base §13.3 (this skill's script-embedded locale mechanism is the equivalent of `i18n.py`).\n\n## Execution Workflow\n\n1. **Detect Platform** — cross-platform `source scripts/cross-platform/_platform-detect.sh` (sets `WB_OS` / `WB_ARCH`; Windows handled inside `.ps1` scripts, no source)\n2. **Pre-scan Confirmation** (only when gate 0 classifies the request as **Complex**) — before a full scan, prompt and wait:\n - Prompt (English by default; auto-switched to Chinese on a `zh-*` locale): \"⚠️ Auto-scan may take a while (~30s on Windows). If you have ≤3 packages, specify paths to skip. Your choice?\" Options: A) Auto-scan B) Specify paths\n - A → step 3; B → skip scan, go to step 4\n3. **System Scan** (only if A) — batch-detect installed software:\n - Windows: `scripts/windows-only/scan/scan_all.ps1`; Mac/Linux: `scripts/cross-platform/scan/scan_all.sh`\n - Output JSON: `{\"R\":{\"installed\":true,\"path\":\"...\",\"version\":\"...\"},...}`\n - **Batch scan** (`scan_all.*`): without explicit consent it is **skipped entirely** (prints a notice, exits 0, no JSON). With consent (set `STATSOFT_AUTO_WRITE` to `1` or `STATSOFT_CONFIRM` to `1` plus an interactive `y`) it returns the full `{path, version}` JSON. `STATSOFT_REVEAL` does **not** affect the batch scan.\n - **Per-software setup** (`setup_*.sh` / `setup_*.ps1`): reports `installed=true` with path / version **hidden by default**; `STATSOFT_REVEAL` set to `1` reveals them in the setup output — this is the only thing `REVEAL` controls.\n4. **Select Config Mode** — batch / specified / single-software (calls individual `setup_*.ps1` or `setup_*.sh`)\n5. **Detect & Setup** — route to the platform script; non-Windows auto-hides incompatible software\n6. **Save Config** — detect-only by default; writes `config.json` only with explicit authorization (set `STATSOFT_AUTO_WRITE` to `1` or `STATSOFT_CONFIRM` to `1` plus an interactive `y`)\n7. **Output Summary** — per `references/completion-prompts.md` template\n\n## Default-Deny Gates\n\nAll persistence and sensitive operations are **off by default** and require explicit authorization (fail-closed), consistent with the scripts:\n\n| Gate | Effect | Default |\n|------|--------|---------|\n| `STATSOFT_AUTO_WRITE` set to `1` | Persist `config.json` (non-interactive / agent context) | off |\n| `STATSOFT_CONFIRM` set to `1` + TTY y | Persist after interactive confirmation | off |\n| `STATSOFT_REVEAL` set to `1` | Reveal path / version in **per-software setup** output only (batch `scan_all` needs consent, not `REVEAL`) | off |\n| `STATSOFT_VERIFY` set to `1` | Allow launching third-party binaries for version / verification | off |\n| `STATSOFT_CMDSTAN_RUN` set to `1` | Allow compiling & running user Stan models (untrusted native code) | off |\n\nAll writes go through `scripts/common/write_config.py`: accepts only the canonical `config.json` under the skill root, and before writing takes a timestamped backup (`config.json.bak.yyyymmdd_hhmmss`) then atomic-replaces.\n\n## Core Permissions\n\n- **Local file read-write** — `config.json`, temp scripts\n- **Process execution** — statistical software binaries\n- **Network access** — CRAN / Anaconda repos\n\n## Trust & Safety\n\nThis skill performs high-risk operations; understand the risk levels before use:\n\n| Risk | Level |\n|------|-------|\n| Execute local executables | 🔴 High |\n| Download & install software | 🔴 High |\n| Execute user scripts (e.g. `.sps` via SPSS Python) | 🔴 High |\n| Modify config.json | 🟡 Medium |\n| Network access | 🟡 Medium |\n\n**Pre-flight**: ✅ review all scripts; ✅ confirm config.json changes (auto-backup); ✅ confirm any downloads; ✅ inspect generated commands for sensitive projects.\n\n## Reference Files\n\n- `ADDITIONAL_SOFTWARE.md` — extended software config (31 packages)\n- `references/command-examples.md` — per-software CLI command examples\n- `references/config-templates.md` — `config.json` templates & field reference\n- `references/version-specifics.md` — version differences\n- `references/completion-prompts.md` — completion prompt templates\n- `references/trust-and-safety.md` — risk levels & pre-flight details\n- `references/workflow.md` — workflow gating details\n- `references/platform-support.md` — full platform support matrix\n- `tests/` — automated test scripts\n\nFile v2.8.2:README.md\n\n# statsoft-cli\n\n[🇨🇳 中文 (Chinese)](./README_zh-CN.md) | [🇬🇧 English (Current)](#)\n\n
\n \"statsoft-cli\n
\n\n> **Cross-platform statistical software CLI integration for your AI Agent**\n>\n> You don't need to learn each tool's CLI — just tell the assistant which statistical software you want to use in plain language, and it detects, configures, and runs them inside your AI workflow. Covers 34+ packages (R, Stata, SAS, SPSS, Python, Bayesian, ML…), bilingual (Chinese / English). By default it only **detects** — it never writes config or runs anything risky without your explicit go-ahead.\n\n---\n\n## 1. How to Use It in a Chat (the Core)\n\nstatsoft-cli is a **conversational skill**: you simply name the tool and the action in natural language — no commands to memorize. As a WorkBuddy skill it **auto-loads with no extra installation**.\n\n> **Quick start:** just name a tool and an action — *\"Connect SPSS 26\"*, *\"Convert data.sav to data.dta\"* — and the assistant detects, configures, and (with your OK) runs it. **It will not push you into a long menu:** a clear request acts immediately; a routing menu only appears when you're undecided (see Examples 4–5).\n\nBelow are real conversational examples ordered from simple to advanced. Each shows **\"You say\"** and a sketch of **\"The assistant replies\"**, plus how to actually trigger the real action.\n\n### Example 1 · Connect a single tool (most common)\n**You say:**\n> Connect SPSS 26\n\n**Assistant replies (sketch):**\n> Scanning for SPSS Statistics… Found it at `C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe` (v26).\n> Detected only — I did not change config.json. To save this, say \"save it\" or set `STATSOFT_AUTO_WRITE` to `1`.\n\n**📌 No menu forced (simple path):** because this is a *simple* request (a named tool + action), the assistant detects and reports directly — no scan/routing menu pops up (see the Clarification Gate in SKILL.md).\n\n**📌 Trigger the real action:** By default only detection runs (fail-closed). To persist the result, say **\"save the config\"** / **\"yes, write it\"** at the prompt, or set `STATSOFT_AUTO_WRITE` to `1`. Execution of syntax / binaries also needs explicit confirmation.\n\n### Example 2 · Run a syntax / convert data\n**You say:**\n> Convert data.sav to data.dta\n\n**Assistant replies (sketch):**\n> I'll use Stat/Transfer for that. Here is the planned command (dry-run shown). Confirm and I'll run it.\n\n### Example 3 · Multi-software workflow\n**You say:**\n> In one session, use R for modeling and SPSS for descriptive stats\n\n### Example 4 · Not sure what's installed (Complex menu)\n**You say:**\n> Set up my statistics tools, but I'm not sure which are installed or which versions I have\n\n**Assistant replies (sketch):**\n> Two ways to proceed — here's a menu:\n> **① How should I find your tools?**\n> - (a) Auto-scan my machine (~30s on Windows) — finds everything\n> - (b) I'll specify the paths myself (faster if you have ≤3)\n>\n> **② Can't decide?** → Say \"what's the difference\" and I'll explain scan vs manual before you choose.\n>\n> Pick ①(a)/(b), or ② to hear the explanation.\n\n**📌 Note:** When you name the goal but are undecided on *method* (scan vs manual paths), the assistant **pops a routing menu** to confirm step by step — instead of deciding for you or dumping a huge list.\n\n### Example 5 · Vague request (grill-me)\n**You say:**\n> I want to use statistical software but don't really know where to start\n\n**Assistant replies (sketch):**\n> Sure — a few quick questions will pin it down:\n> 1. Which tool(s) do you actually have installed (R / SPSS / Stata / SAS / other)?\n> 2. What do you want to do — run old scripts, convert data, or build a new analysis?\n> 3. Do you need it headless (command line) or is a GUI fine?\n>\n> (After you answer, the assistant keeps probing until the right tool is locked, then configures it.)\n\n**📌 Note:** When you say \"not sure\", the assistant uses **branch-by-branch probing** instead of dumping the 34-tool list or picking for you.\n\n> 💡 **Language:** On a Chinese-locale system the assistant replies in Chinese; otherwise English. You can force-switch anytime (e.g. \"用中文回复\" / \"switch to English\").\n\n---\n\n## 2. What You Can Do — 34+ Packages\n\n| What you can do | Typical scenario | Try saying in chat |\n|:---|:---|:---|\n| Configure & detect a tool | SPSS / R / Stata / SAS / Mplus / CmdStan … | \"Connect SPSS 26\" |\n| Run syntax / scripts | `.sps` / `.do` / `.sas` / `.R` via the tool's engine | \"Run my Stata do-file in batch\" |\n| Convert data formats | Stat/Transfer migrates SAS ↔ SPSS ↔ Stata ↔ Excel | \"Convert data.sav to data.dta\" |\n| Multi-software mix | R modeling + SPSS descriptive + Stata prep in one session | \"Use R for modeling and SPSS for descriptives\" |\n| Reuse historical code | Bring old R scripts / SPSS syntax / SAS macros into the workflow | \"Wire my old R scripts into the workflow\" |\n| GUI-only launch guide | AMOS / GraphPad / JASP / jamovi / Minitab — detect + manual launch | \"How do I launch JASP?\" |\n\nTools are auto-routed by platform; non-Windows auto-hides incompatible software. The full matrix is in the [Advanced Reference](ADVANCED.md).\n\n---\n\n## 3. First-Time FAQ\n\n**Q: Does it modify config.json automatically?**\nA: No. Detection is the default — it only reports what it finds. Writing config.json requires your explicit opt-in (set `STATSOFT_AUTO_WRITE` to `1`, or answering `y` at the prompt).\n\n**Q: Will it run my software or send data anywhere without asking?**\nA: No. Every execution, install, network fetch, and persistent write needs explicit confirmation or an opt-in flag. Read-only detection is the default.\n\n**Q: Does it drive GUI-only software (AMOS, GraphPad, JASP, jamovi, Minitab)?**\nA: No. These are detected and given a manual launch guide only; the skill never drives them via CLI / headless (e.g. `mtb.exe /run` opens the Minitab GUI, not headless).\n\n**Q: Is the output in Chinese on a Chinese system?**\nA: Yes. Output language follows your OS locale by default; you can force-switch anytime via a prompt.\n\n**Q: Do I need network access?**\nA: Offline by default. Network is used only to install local dependencies (R packages / software) and only with your explicit confirmation.\n\n---\n\n## 4. Safety & Disclaimer\n\n- **Fail-closed by default:** All persistence and sensitive operations are **off unless you explicitly authorize** them. Five gates (`STATSOFT_AUTO_WRITE` / `STATSOFT_CONFIRM` / `STATSOFT_REVEAL` / `STATSOFT_VERIFY` / `STATSOFT_CMDSTAN_RUN`) guard config writes, detail disclosure, binary launches, and untrusted native-code (Stan) compilation.\n- **Detection-only default:** Scanning reports only a boolean `installed` unless you opt into path/version disclosure.\n- **Local only:** No user data leaves your machine. Network use is limited to reading public docs / installing local dependencies, disclosed per action.\n- For details see [ADVANCED.md](ADVANCED.md) → Trust & Safety.\n\n---\n\n## 5. Advanced Reference (for developers)\n\nCLI commands, the full platform-support matrix, project structure, activation boundary, and detailed Trust & Safety have moved to **[ADVANCED.md](ADVANCED.md)**. Ordinary users don't need it; Sections 1–4 cover daily use.\n\n---\n\n**Version**: v2.8.0 | **License**: MIT | **Authors**: medstatstar, phoe-zip\n\nFor feature requests, bug reports, or other feedback, please contact the author directly at medstatstar@gmail.com (Wintone Zhang / 张文彤).\n\nFile v2.8.2:tests/README.md\n\n# SPSS Splash-free Call Test / SPSS 无闪屏调用测试\n\n## Test Purpose\n\n验证 SPSS 无闪屏调用方式是否正常工作。\n\nVerify that the SPSS splash-free call method works correctly.\n\n> ⚠️ **副作用提示 / Side effects**：运行本测试会**执行第三方 SPSS 二进制**，并在磁盘上**写入文件** `test-data.sav`（约 5 条记录）。这是测试的预期产物，仅供手动执行；请勿在自动化流程中静默运行。测试完成后请参见文末「清理 / Cleanup」删除该文件。\n>\n> Running this test **executes the third-party SPSS binary** and **writes a file** `test-data.sav` (~5 rows) to disk. This is an expected artifact of a manually-run test — do not run it silently in automation. See \"Cleanup\" at the end to remove it afterward.\n\n## Test Method\n\n### Preferred Method (Completely Splash-free)\n\n使用 SPSS 内置 Python 的 `spss` 模块直接运行语法，不调用 `stats.exe`，完全无 GUI。\n\nUse SPSS built-in Python's `spss` module to run syntax directly, without calling `stats.exe`, completely GUI-free.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[SPSS_PYTHON_PATH]\" \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" run-internal \"[SPS_FILE]\"\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\Python3\\python.exe\" \\\n \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" \\\n run-internal \\\n \"[SKILL_DIR]/tests/test-syntax.sps\"\n```\n\n### Backup Method (No Splash)\n\n通过 `stats.com`（控制台版）调用 .spj 文件，完全无闪屏：\n\n```bash\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.com\" -production silent -nologo \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n`stats.com` 控制台版纯后台运行，绝无闪屏。\n\n最后备选（可能有闪屏）： `stats.exe -production silent -nologo`。\n\nCall .spj file via `stats.exe -production`. This method may display splash screen.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[STATS_EXE_PATH]\" -production \"[SPJ_FILE]\" silent -nologo\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe\" \\\n -production \\\n \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n## Test Files\n\n- `test-syntax.sps` — SPSS 语法文件，生成测试数据并保存\n- `test-job.spj` — SPSS 生产作业文件（备用方式使用）\n\n## Expected Results\n\n1. **无闪屏** — 运行时不显示 SPSS GUI 窗口\n2. **输出文件生成** — 生成 `test-data.sav` 文件\n3. **数据正确** — `test-data.sav` 包含 5 条记录，id 和 score 两列\n\n## Verification Method\n\n```bash\n# 检查输出文件是否生成\nls -la \"[SKILL_DIR]/test-data.sav\"\n\n# 读取 .sav 文件内容（需要 pyreadstat）\npython -c \"\nimport pyreadstat\ndf, meta = pyreadstat.read_sav('[SKILL_DIR]/test-data.sav')\nprint(df)\n\"\n```\n\n## Cleanup\n\n测试会写入 `test-data.sav`。测试完成后删除该文件即可清除所有磁盘副作用 / The test writes `test-data.sav`; delete it after the test to remove all disk side effects:\n\n```bash\nrm -f \"[SKILL_DIR]/test-data.sav\"\n```\n\n## Notes\n\n1. SPSS 26 内置 Python 3.4，不支持 f-string，所有字符串格式化必须用 `%s` 或 `.format()`\n2. 确保输出路径有写权限\n3. 如果测试失败，检查 SPSS 安装路径是否正确\n\nFile v2.8.2:_meta.json\n\n{\n \"ownerId\": \"kn7amqq1jv28skb63wavr6shah89jsm5\",\n \"slug\": \"statsoft-cli\",\n \"version\": \"2.8.2\",\n \"publishedAt\": 1785672882418\n}\n\nFile v2.8.2:references/command-examples.md\n\n# Command Invocation Examples\n\n> This document contains CLI command invocation examples for each statistical software package.\n\n---\n\n## Table of Contents\n\n1. [R](#r)\n2. [SPSS](#spss)\n3. [Stata](#stata)\n4. [SAS](#sas)\n5. [JMP](#jmp)\n6. [GraphPad Prism](#graphpad)\n7. [Stat/Transfer](#stattranfer)\n8. [Other software](#others)\n9. [JAGS](#jags)\n10. [SHAZAM](#shazam)\n11. [OxMetrics](#oxmetrics)\n12. [TSP](#tsp)\n13. [Tanagra](#tanagra)\n14. [Orange](#orange)\n15. [H2O.ai](#h2o)\n16. [GenStat](#genstat)\n17. [Rattle](#rattle)\n18. [OpenBUGS](#openbugs)\n19. [LIMDEP](#limdep)\n20. [NLOGIT](#nlogit)\n21. [Microfit](#microfit)\n\n---\n\n## R\n\n### Basic run\n\n```bash\n# Run R script\nRscript --vanilla \"script.R\"\n\n# Use R CMD BATCH (generates .Rout file)\nR CMD BATCH \"script.R\" \"output.Rout\"\n```\n\n### Package installation (requires explicit user confirmation before network download/install)\n\n```bash\n# Downloads from CRAN and modifies the local R environment; requires explicit user confirmation before running — do not install without it\nRscript -e \"install.packages('pkg', repos='https://cran.r-project.org')\"\n```\n\n### Batch script template\n\n```r\n# script.R\noptions(warn=-1)\nlibrary(dplyr)\n\ndata <- read.csv(\"data.csv\", fileEncoding=\"UTF-8\")\nresult <- lm(y ~ x1 + x2, data=data)\nsummary(result)\n\nwrite.csv(result$coefficients, \"results.csv\", row.names=FALSE)\nsave(result, file=\"results.RData\")\n```\n\n### Common scenarios\n\n```bash\n# Read SPSS .sav file\nRscript -e \"library(haven); df <- read_sav('data.sav'); print(head(df))\"\n\n# Generate HTML report\nRscript -e \"rmarkdown::render('report.Rmd', output_file='report.html')\"\n\n# Large data processing\nRscript -e \"library(arrow); df <- read_parquet('big_data.parquet'); print(dim(df))\"\n```\n\n---\n\n## SPSS\n\n### 🎯 Usage Recommendation\n\n> **For daily complex syntax runs** → **use Approach 1** (`stats.com` + `.spj`, foolproof)\n>\n> **Approach 2** (internal Python driver) **can only run pure analysis syntax** and **must not contain** the following commands:\n> - ❌ `OUTPUT SAVE`\n> - ❌ `OUTPUT EXPORT` / `OUTPUT DISPLAY`\n> - ❌ `HOST COMMAND`\n> - ❌ `XDATA` / `XSAVE` (when OUTPUT objects are involved)\n>\n> — When unsure whether a command involves OUTPUT/SAVE, use Approach 1 (`.spj`) for safety.\n\n---\n\n### ⭐ Preferred approach (completely splash-free)\n\nRun directly through the SPSS built-in Python `spss` module:\n\n```bash\n# Invoke via spss_helper.py\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\Python3\\python.exe\" \\\n \"C:\\path\\to\\statsoft-cli\\windows-only\\SPSS\\spss_helper.py\" \\\n run-internal \"C:\\path\\to\\syntax.sps\"\n```\n\n**Call chain**:\n```\nAI Agent (Bash tool)\n → python.exe spss_helper.py run-internal \n → subprocess.run([stats_python_path, helper_script], creationflags=0x08000000)\n → SPSS runs in background (zero window)\n```\n\n### Fallback approach\n\nRun the .spj file via `stats.com` (console version, completely splash-free):\n\n```bash\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\stats.com\" -production silent -nologo \"job.spj\"\n```\n\nOr use `stats.exe` (GUI version, may show a splash screen):\n\n```bash\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\stats.exe\" -production \"job.spj\" silent -nologo\n```\n\n### .spj file XML structure\n\n```xml\n\n\n \n \n \n\n```\n\n**Key**: the `` element must not be omitted, otherwise a NullPointerException is thrown.\n\n### Automated Python script (completely GUI-free)\n\n```python\nimport sys, os\n\n# 1. Configure paths\nspss_python_path = r\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\Python3\\python.exe\"\nsps_file = r\"project\\analysis.sav\"\noutput_sav = r\"project\\results.sav\"\n\n# 2. Generate SPSS syntax\nsps_syntax = \"\"\"\nGET FILE='data.sav'.\nCOMPUTE new_var = var1 + var2.\nSAVE OUTFILE='{out}'.\n\"\"\".format(out=output_sav.replace(\"\\\\\", \"/\"))\n\n# 3. Run via SPSS built-in Python (completely GUI-free)\nspss_pkg = os.path.join(os.path.dirname(spss_python_path), \"Lib\", \"site-packages\")\nsys.path.insert(0, spss_pkg)\n\nimport spss\nspss.StartSPSS()\nprint(\"SPSS processor started (no GUI)\")\n\n# Submit syntax\nspss.Submit(sps_syntax)\nprint(\"Syntax executed\")\n\nspss.StopSPSS()\nprint(\"SPSS processor stopped\")\n\n# 4. Read results (using Anaconda Python's pyreadstat)\nimport pyreadstat\ndf, meta = pyreadstat.read_sav(output_sav)\nprint(df.head())\n```\n\n---\n\n## SPSS Modeler\n\n### Batch execute .str stream file\n\n```powershell\n# Via statsoft-modeler CLI\nstatsoft-modeler run \"C:\\path\\to\\churn_model.str\"\n\n# Or call clemb.exe directly\n& \"C:\\Program Files\\IBM\\SPSS\\Modeler\\18.0\\bin\\clemb.exe\" -local -stream \"churn_model.str\" -log \"run.log\" -execute\n```\n\n### Python script mode (recommended)\n\n```powershell\n# Run Python script (within Modeler session)\nstatsoft-modeler run-script \"C:\\path\\to\\train_model.py\"\n\n# Equivalent to clemb command\n& \"C:\\Program Files\\IBM\\SPSS\\Modeler\\18.0\\bin\\clemb.exe\" -local `\n -script \"train_model.py\" -scriptlang python `\n -log \"train.log\" -execute\n```\n\n### Remote Modeler Server mode (not supported)\n\n> ⚠️ This skill does NOT support remote Modeler Server execution. `statsoft-modeler` provides LOCAL (`-local`) mode only — there is no `server-run` subcommand, and the skill never initiates remote connections or handles remote credentials.\n\n### Python script example (run within Modeler)\n\n```python\n# train_model.py — SPSS Modeler Python script\nimport modeler.api\n\n# Get current session\nsession = modeler.api.GetSession()\n\n# Load stream file\nstream = session.LoadStream(\"churn_model.str\")\n\n# Set parameters\nstream.SetVariable(\"data_path\", \"C:/data/customer.csv\")\n\n# Execute stream\nstream.Execute()\n\n# Export results\noutput_node = stream.FindNode(\"table_output\")\noutput_node.Export(\"C:/output/results.csv\")\n```\n\n---\n\n## Stata\n\n### ⚠️ Version and parameter reference table\n\n| Version | Windows silent flag | Mac/Linux silent flag |\n|------|-----------------|-------------------|\n| **Stata ≤ 12** | `StataMP /e do \"script.do\"` | `stata-mp -e do \"script.do\"` |\n| **Stata ≥ 13** | `StataMP /b do \"script.do\"` | `stata-mp -b do \"script.do\"` |\n\n**Key**: Stata 12 uses `-e`, Stata 13+ uses `-b`. Using the wrong version parameter triggers a confirmation dialog!\n\n### Basic batch example\n\n```bash\n# Stata 13+ (Windows)\n\"C:\\Program Files\\Stata17\\StataMP-64.exe\" /b do \"script.do\"\n\n# Stata 13+ (Mac/Linux)\nstata-mp -b do \"script.do\"\n\n# Stata 12 and earlier (Windows) — /b not supported!\n\"C:\\Program Files\\Stata12\\StataMP.exe\" /e do \"script.do\"\n\n# Stata 12 and earlier (Mac/Linux) — -b not supported!\nstata-mp -e do \"script.do\"\n```\n\n### Version and executable file reference\n\n| Version | MP | SE | BE |\n|------|----|----|-----|\n| Stata 12 and earlier | `StataMP` | `StataSE` | `Stata` |\n| Stata 14/15 | `StataMP` | `StataSE` | `Stata` |\n| Stata 16+ | `StataMP-64.exe` | `StataSE-64.exe` | `Stata-64.exe` |\n\n### do-file template\n\n```stata\n* script.do — Stata batch script\ncd \"workdir\"\nuse \"data.dta\", clear\nregress y x1 x2\nsave \"results.dta\", replace\nlog using \"results.log\", replace\nsummarize\nlog close\n```\n\n---\n\n## SAS\n\n### Basic batch\n\n```bash\n# Windows\n\"C:\\Program Files\\SASFoundation\\9.4\\sas.exe\" -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"\n\n# Mac/Linux\nsas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"\n```\n\n### SAS program template\n\n```sas\n* prog.sas — SAS batch program;\noptions ls=80 ps=60 nodate nonumber encoding='utf-8';\n\n* Read data;\ndata work.data;\n infile \"data.csv\" dlm=',' firstobs=2;\n input var1 var2 var3;\nrun;\n\n* Analysis;\nproc reg data=work.data;\n model y = var1 var2;\nrun;\n\n* Save results;\nproc export data=work.result\n outfile=\"results.csv\"\n dbms=csv replace;\nrun;\n```\n\n---\n\n## JMP\n\n### Basic batch\n\n```powershell\n# Batch mode (may show brief splash screen 1-2 seconds)\n& \"C:\\Program Files\\JMP\\16\\JMP.exe\" /R \"script.jsl\"\n```\n\n⚠️ JMP script must end with `Exit();`\n\n### JSL script template\n\n```jsl\n// script.jsl — JMP batch script\ndt = Open(\"data.jmp\");\ndt << Fit Y( :Y Column ) X( :X Column );\nSave PDF(\"report.pdf\");\nClose(dt, \"Yes\");\nExit();\n```\n\n---\n\n## GraphPad Prism\n\n⚠️ **Important limitation (GUI-only, out of scope)**: GraphPad Prism **has no CLI mode**; invocation always pops up the GUI, unavoidable.\n\n**This skill's capability for Prism is limited to**:\n- Detecting whether Prism is installed locally;\n- Providing **guidance to manually launch the GUI** (you open Prism yourself).\n\n**This skill explicitly does NOT do the following** (even after opt-in):\n- Does not call `prism.exe` from the command line or automate/drive the Prism process in any way;\n- **Does not create, read, or modify any Prism-related files (including `.pzfx` project/data files)**.\n\n> Note: `.pzfx` is an XML format; third-party pure-Python libraries (e.g., `prismWriter`) can parse/generate it. Such file read/write **is not part of this skill's allowed behavior** — this skill does not wrap, call, or perform such write operations. If you truly need it, use the relevant library manually outside this skill and take responsibility for the file writes yourself.\n\n---\n\n## StatTransfer\n\n### Single-file conversion\n\n```bash\n# SPSS → Stata\nst in.sav out.dta\n\n# CSV → SPSS\nst in.csv out.sav\n\n# SAS → R\nst in.sas7bdat out.rda\n```\n\n### Batch conversion\n\n```bash\n# Batch-convert all .sav in a directory to .dta\nst in\\*.sav out\\*.dta\n\n# Command-file batch processing\nst myfile.stcmd\n```\n\n---\n\n## Other software\n\n### Gretl\n\n```bash\n# Run gretl script in batch mode\ngretlcli -b script.inp\n```\n\n### Mathematica\n\n```bash\n# Run Wolfram Language script\nwolframscript -file script.wl\n\n# Execute code directly\nwolframscript -code \"Table[i^2, {i, 10}]\"\n\n# Load data and analyze\nwolframscript -code \"data = Import[\\\"data.csv\\\"]; Mean[data]\"\n\n# Symbolic computation\nwolframscript -code \"D[x^3 + 2x^2 + 5, x]\"\n\n# Statistical modeling\nwolframscript -code \"data = RandomVariate[NormalDistribution[], 1000]; DistributionFitTest[data, Automatic]\"\n\n# Generate image\nwolframscript -code \"p = Plot[Sin[x], {x, 0, 6 Pi}, PlotLabel -> \\\"Sine Wave\\\"]; Export[\\\"sine.png\\\", p]\"\n\n# Windows explicit MathKernel call (alternative to wolframscript)\n\"C:\\Program Files\\Wolfram Research\\Mathematica\\14.0\\MathKernel.exe\" -noprompt < script.m\n```\n\n### Minitab\n\n> ⚠️ **Minitab is GUI-only for automation.** `mtb.exe /run \"script.mtb\"` launches the full Minitab GUI window (not headless) and may hang. Do **not** drive Minitab from the agent — detect the install and let the user run analyses interactively.\n\n```powershell\n# Detection only — verify mtb.exe exists; do NOT call /run headlessly\n$mtb = \"C:\\Program Files\\Minitab\\Minitab 22\\mtb.exe\"\nif (Test-Path $mtb) { Write-Host \"Minitab detected: $mtb\" }\n```\n\nFor actual analysis, open Minitab (GUI) and load your `.mtb` / `.mpj` project, or use the Minitab Web App (https://app.minitab.com/).\n\n### Matlab\n\n```bash\n# Completely GUI-free batch\nmatlab -batch \"run('script.m'); exit\"\n```\n\n### Julia\n\n```bash\njulia script.jl\n```\n\n### EViews\n\n```powershell\n# EViews batch\n& \"C:\\Program Files\\QMS\\EViews 12\\EViews12_x64.exe\" /b \"program.prg\"\n```\n\n### Statistica\n\n```powershell\n# Statistica Visual Basic script\n& \"C:\\Program Files\\StatSoft\\Statistica 13\\Statistica.exe\" /s \"script.svb\"\n```\n\n---\n\n## JAGS\n\n### Basic batch\n\n```bash\n# Run JAGS script\njags scriptfile\n\n# Batch execution\njags-script script.txt\n\n# Via R interface\nRscript -e \"library(rjags); jags.model('script.dat', data)\"\n```\n\n---\n\n## SHAZAM\n\n### Basic batch\n\n```bash\n# Run SHAZAM command file\nshazam commands.txt\n\n# Sample command file:\n# /MODEL TITLE MYMODEL\n# / X 1 100\n# / PREDICT Y\n# /END\n```\n\n---\n\n## OxMetrics\n\n### Basic batch\n\n```bash\n# Show CLI options\noxmetrics --help\n\n# Run batch\noxmetrics -b commands.txt\n```\n\n---\n\n## TSP\n\n### Basic batch\n\n```bash\n# Run TSP command file\ntsp commands.txt\n```\n\n---\n\n## Tanagra\n\n### Basic batch\n\n```bash\n# Show CLI options\ntanagra --help\n\n# Execute batch script\ntanagra -f script.txt\n```\n\n---\n\n## Orange\n\n### Python module approach (recommended)\n\n```bash\n# Via Python module\npython3 -m Orange.canvas\n\n# Install (requires network; modifies local Python environment; run only after explicit user confirmation)\n# Install (requires network access and modifies the local Python environment; run ONLY after explicit user confirmation)\npip install orange3\n# or\nconda install -c conda-forge orange3\n```\n\n---\n\n## H2O.ai\n\n### Python approach (recommended)\n\n> ⚠️ **Network & download note**: `h2o.init()` / `h2o start` starts a **local web server** on this machine (default port 54321, browser-accessible); the first run **downloads components** over the network; `pip install h2o` also requires network access. Before starting the H2O server, the Agent must explain this network behavior to the user and obtain explicit confirmation, and must never expose the port to the public internet.\n\n```bash\n# ⚠️ This starts a local H2O server (JVM, binds a port). Requires explicit per-run opt-in.\n# Start H2O server (local HTTP service, default port 54321)\nh2o start\n\n# ⚠️ This starts a local H2O server (JVM, binds a port). Requires explicit per-run opt-in.\n# Via Python\npython3 -c \"import h2o; h2o.init()\"\n\n# Install (requires network)\npip install h2o\n```\n\n---\n\n## GenStat\n\n### Basic batch\n\n```bash\n# Run GenStat command file\ngenstat commands.txt\n```\n\n---\n\n## Rattle\n\n### CLI mode\n\n```bash\n# CLI mode\nrattle --cli\n\n# Via R package\nRscript -e \"library(rattle); rattle()\"\n```\n\n---\n\n## OpenBUGS\n\n### Basic batch\n\n```bash\n# Show help\nopenbugs --help\n\n# Batch execution\nopenbugs -b script.txt\n```\n\n---\n\n## LIMDEP\n\n### Basic batch\n\n```batch\nREM Run LIMDEP command file\nlimdep commands.txt\n```\n\n---\n\n## NLOGIT\n\n### Basic batch\n\n```batch\nREM Run NLOGIT command file\nnlogit commands.txt\n```\n\n---\n\n## Microfit\n\n### Basic batch\n\n```batch\nREM Run Microfit command file\nmicrofit commands.txt\n```\n\n---\n\n## NCSS\n\n### Basic batch\n\n```batch\nREM Run NCSS batch analysis\n\"NCSS.exe\" /B \"analysis.ncss\"\n\nREM Generate NCSS report\n\"NCSS.exe\" /B \"report.ncss\"\n```\n\n### Analysis script template\n\n```\n[Analysis]\nProcedure = Descriptive Statistics\nVariables = Age, Height, Weight\n\n[Output]\nExport = \"results.html\"\n```\n\n---\n\n## Origin (OriginLab)\n\n### Run LabTalk script\n\n```batch\nREM Run LabTalk batch script\n\"C:\\Program Files\\OriginLab\\Origin2025\\origin97.exe\" -h \"script.ogs\"\n```\n\n### LabTalk script template\n\n```labtalk\n// script.ogs — Origin LabTalk script\nimpASC fname:=\"C:\\data\\data.csv\";\nrange rr = col(1);\ninteg1 rr;\ntype \"Mean: $(mean(rr))\";\ndoc -e P \"C:\\output\\result.png\";\nexit;\n```\n\nFile v2.8.2:references/completion-prompts.md\n\n# Configuration Completion Prompts\n\n> This document was extracted when SKILL.md was streamlined; it contains completion-prompt templates for each statistical software configuration.\n> After software detection completes, the AI should output completion notices to the user following the templates below.\n\n---\n\n## SPSS\n\n> ⚠️ **Important — daily usage recommendation**:\n> - **For complex syntax runs → use Approach 1** (`stats.com` + `.spj`, foolproof)\n> - **Approach 2** (internal Python driver) **can only run pure analysis syntax** and must not contain:\n> - `OUTPUT SAVE`, `OUTPUT EXPORT`, `OUTPUT DISPLAY`\n> - `HOST COMMAND`, `XDATA`, `XSAVE` (when OUTPUT objects are involved)\n> - When unsure whether a command involves OUTPUT/SAVE → use Approach 1 (`.spj`) uniformly\n>\n> See SKILL.md core permissions section (Core Permissions) for SPSS invocation details.\n\n---\n\n## SPSS Modeler\n\n- ✅ SPSS Modeler supports pure CLI execution via `clemb.exe`, completely GUI-free, no splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for data mining, predictive modeling, ML pipelines\n\n---\n\n## Stata\n\n```\n✅ Stata association configuration complete!\n\n⚠️ Important notes:\n 1. **⚠️⚠️ Stata version and batch parameters (important)**:\n - **Stata 12 and earlier** → Windows: `/e do \"script.do\"`, Mac/Linux: `-e do \"script.do\"`\n - **Stata 13 and later** → Windows: `/b do \"script.do\"`, Mac/Linux: `-b do \"script.do\"`\n - ❌ **Wrong version parameter triggers a confirmation dialog!**\n 2. Paths containing spaces must be wrapped in double quotes, otherwise a file not found error occurs\n 3. **License match**: when invoking Stata you must use the executable matching the license\n - MP license → use StataMP-64.exe (Windows) or stata-mp (Mac/Linux)\n - SE license → use StataSE-64.exe (Windows) or stata-se (Mac/Linux)\n - BE license → use Stata-64.exe (Windows) or stata (Mac/Linux)\n - ❌ If the wrong edition is used (e.g., MP binary without an MP license), Stata fails to start or errors out\n 4. **Edition feature differences**:\n - MP (Multiprocessing): multi-core parallelism, good for large data\n - SE (Special Edition): single-core, good for medium data\n - BE (Basic Edition): limited features, no parallelism\n 5. **Version-specific changes**:\n - Stata 14/15: executables named StataMP, StataSE (no -64 suffix)\n - Stata 16+: executables named StataMP-64, StataSE-64 (added -64 suffix)\n - Stata 16+: supports Python integration (call Python from Stata)\n - Stata 17+: introduced PyStata (call Stata from Python)\n - Stata 19+: introduced StataNow rapid-update mechanism\n 6. **Windows install path differences**:\n - Stata 14-18: `C:\\Program Files\\StataNN` (NN is the version number)\n - Stata 19: `C:\\Program Files\\Stata19` or `C:\\Program Files\\StataNow19`\n\n📋 Recommended usage:\n # Windows (choose correct edition by license)\n \"StataMP-64.exe\" /b do \"script.do\" # MP edition (Stata 16+)\n \"StataSE-64.exe\" /b do \"script.do\" # SE edition (Stata 16+)\n \"Stata-64.exe\" /b do \"script.do\" # BE edition (Stata 16+)\n \"StataMP\" /b do \"script.do\" # MP edition (Stata 14/15)\n\n # Mac/Linux (choose correct edition by license)\n stata-mp -b do \"script.do\" # MP edition\n stata-se -b do \"script.do\" # SE edition\n stata -b do \"script.do\" # BE edition\n```\n\n---\n\n## R\n\n```\n✅ R connection configuration complete!\n\n⚠️ Important notes:\n 1. Use Rscript command for batch mode, not R GUI\n 2. Installing R packages requires EXPLICIT user confirmation (downloads from CRAN, modifies local environment) before proceeding — do not install without it\n 3. Chinese encoding issues: use fileEncoding=\"UTF-8\" parameter\n 4. Insufficient memory: use data.table or arrow packages for large data\n\n📋 Recommended usage:\n Rscript --vanilla \"script.R\"\n\n # Package installation (requires explicit user confirmation before network download)\n Rscript -e \"cat('Installing package from CRAN (requires network access)...\\n'); install.packages('[PKG]', repos='https://cran.r-project.org')\"\n\n # Read SPSS .sav file\n Rscript -e \"library(haven); df <- read_sav('data.sav'); print(head(df))\"\n\n💡 Alternatives without R:\n If R is not installed, consider using Anaconda Python environment:\n - dplyr / tidyr → pandas\n - ggplot2 → matplotlib / seaborn\n - caret / xgboost → scikit-learn\n - survival → lifelines\n - lme4 / nlme → statsmodels\n - metafor → PyMC\n```\n\n---\n\n## SAS\n\n```\n✅ SAS connection configuration complete!\n\n⚠️ Important notes:\n 1. Batch mode generates .log (log) and .lst (output listing) files, ensure write permissions\n 2. Chinese encoding: add options encoding='utf-8'; at beginning of program\n 3. SAS license expiration will cause ERROR: License expired\n\n📋 Recommended usage:\n # Windows\n \"sas.exe\" -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"\n\n # Mac/Linux\n sas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"\n```\n\n---\n\n## JMP\n\n- ⚠️ JMP may display a brief splash screen (1-2 seconds), cannot be fully avoided\n- ⚠️ Script must end with `Exit();` or JMP GUI will remain open\n\n> See [ADDITIONAL_SOFTWARE.md → JMP](../ADDITIONAL_SOFTWARE.md#jmp) for details\n\n---\n\n## GraphPad Prism\n\n- ⚠️⚠️⚠️ GraphPad Prism **has no CLI mode**; invocation pops up the GUI (unavoidable)\n- ⚠️ When used, the following occurs: GUI pops up on invocation, user must operate manually\n- 🖱️ This skill only provides **detection + manual GUI-launch guidance**; it does not drive batch processing via CLI/headless\n\n**Parsing-only alternative**:\n| Approach | Description |\n|------|------|\n| Python `prismWriter` library | Can **parse** .pzfx structure (read/validate) without launching the GUI; the library itself also has the ability to **generate** .pzfx, but this skill **never calls or wraps any of its write operations** (consistent with command-examples.md: .pzfx read/write is outside this skill's allowed scope; if needed, do it manually outside this skill and take responsibility) |\n\n> See [ADDITIONAL_SOFTWARE.md → GraphPad Prism](../ADDITIONAL_SOFTWARE.md#graphpad-prism) for details\n\n---\n\n## Stat/Transfer\n\n- ✅ Stat/Transfer is a pure CLI tool, completely GUI-free, suitable for automation\n- ⚠️ Before conversion, confirm the target format supports the required data types\n\n> See [ADDITIONAL_SOFTWARE.md → Stat/Transfer](../ADDITIONAL_SOFTWARE.md#stattransfer)\n\n---\n\n## Gretl\n\n- ✅ Gretl is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Free software, suitable for econometric analysis\n- 💡 Supports reading Stata .dta, SAS .sas7bdat, Excel .xlsx, etc.\n\n> See [ADDITIONAL_SOFTWARE.md → Gretl](../ADDITIONAL_SOFTWARE.md#gretl)\n\n---\n\n## Minitab\n\n- ⚠️ Minitab batch mode may show a brief splash screen\n- ⚠️ Ensure the license is valid\n- 💡 Suitable for quality control and Six Sigma projects\n\n> See [ADDITIONAL_SOFTWARE.md → Minitab](../ADDITIONAL_SOFTWARE.md#minitab)\n\n---\n\n## Matlab\n\n- ✅ Completely GUI-free when using `-batch` parameter\n- ⚠️ Requires Statistics and Machine Learning Toolbox\n- 💡 Suitable for engineering statistics, signal processing, and ML\n\n> See [ADDITIONAL_SOFTWARE.md → Matlab](../ADDITIONAL_SOFTWARE.md#matlab) for details\n\n---\n\n## Mathematica\n\n- ✅ Mathematica is a pure CLI tool (`wolframscript`), completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- 💡 Suitable for symbolic mathematics, numerical analysis, statistical modeling, and visualization\n- ⚠️ WolframScript requires a commercial license with periodic activation\n\n> See [ADDITIONAL_SOFTWARE.md → Mathematica](../ADDITIONAL_SOFTWARE.md#mathematica) for details\n\n---\n\n## Julia\n\n- ✅ Julia is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ High performance, suitable for big data and complex statistical computing\n- 💡 Common packages: Statistics, HypothesisTests, GLM, Turing (Bayesian)\n\n> See [ADDITIONAL_SOFTWARE.md → Julia](../ADDITIONAL_SOFTWARE.md#julia) for details\n\n---\n\n## EViews\n\n- ⚠️ EViews batch mode may show a splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for time-series analysis, regression, and forecasting\n\n> See [ADDITIONAL_SOFTWARE.md → EViews](../ADDITIONAL_SOFTWARE.md#eviews)\n\n---\n\n## Statistica\n\n- ⚠️ Statistica batch mode may show a splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for data mining, machine learning, and statistical analysis\n\n> See [ADDITIONAL_SOFTWARE.md → Statistica](../ADDITIONAL_SOFTWARE.md#statistica)\n\n---\n\n## JAGS\n\n- ✅ JAGS is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ⚠️ If invoked via the `rjags` R package, R and the rjags package must be installed first\n- 💡 Suitable for Bayesian hierarchical models, MCMC simulation\n\n📋 Recommended usage:\n jags scriptfile\n\n💡 Via R interface:\n Rscript -e \"library(rjags); jags.model('script.dat', data)\"\n\n---\n\n## SHAZAM\n\n- ✅ SHAZAM is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ⚠️ Windows version requires a valid license file\n- 💡 Suitable for econometrics, time series, hypothesis testing\n\n📋 Recommended usage:\n shazam commands.txt\n\n---\n\n## OxMetrics\n\n- ✅ OxMetrics is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ⚠️ License file required\n- 💡 Suitable for econometrics, time series, forecasting\n\n📋 Recommended usage:\n oxmetrics --help # view options\n oxmetrics -b commands.txt # batch\n\n---\n\n## TSP\n\n- ✅ TSP is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ⚠️ License file required\n- 💡 Suitable for time-series analysis, econometrics, hypothesis testing\n\n📋 Recommended usage:\n tsp commands.txt\n\n---\n\n## Tanagra\n\n- ✅ Tanagra is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- 💡 Suitable for clustering, classification, association rules, feature selection\n\n📋 Recommended usage:\n tanagra --help # view options\n tanagra -f script.txt # batch script\n\n---\n\n## Orange\n\n- ⚠️ Orange **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Recommended to call in the background via the Python module (no GUI needed)\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n\n**Pure CLI alternative (Python)**:\n```python\n# Run Orange analysis script in background, no GUI needed\nfrom Orange.data import Table\nfrom Orange.classification import RandomForestLearner\n\ndata = Table(\"data.csv\")\nlearner = RandomForestLearner()\nmodel = learner(data)\npredictions = model(data)\n```\n\n📋 Recommended usage:\n python3 -m Orange.canvas # GUI mode\n python3 script.py # Python script mode (recommended, no GUI)\n\n---\n\n## H2O.ai\n\n- ✅ H2O can run in the background via Python, no GUI popup\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free (AutoML fully free)\n- ⚠️ Requires Java (JVM)\n- ⚠️ First start downloads components\n- 💡 Suitable for large-scale ML, AutoML, deep learning\n\n📋 Recommended usage (Python):\n\n> ⚠️ **Security note**: `h2o.init()` launches a local H2O server (a JVM process) and may open a listening port (default 54321); `h2o.import_file(\"data.csv\")` transfers your dataset contents into that service. Require explicit user confirmation before running — never auto-execute.\n\n```python\nimport h2o\nh2o.init() # launches local H2O server (JVM)\nh2o.import_file(\"data.csv\") # uploads dataset into the H2O service\n# ... AutoML training ...\nh2o.shutdown() # shut down the server\n```\n\n⚠️ Notes:\n - If default port 54321 is occupied, use `h2o.init(port=54322)`\n - If memory is insufficient, set `h2o.init(max_mem_size=\"4G\")`\n\n---\n\n## GenStat\n\n- ✅ GenStat is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ⚠️ License file required\n- 💡 Suitable for mixed models, experimental design, REML, spatial analysis, Meta analysis\n\n📋 Recommended usage:\n genstat commands.txt\n\n---\n\n## Rattle\n\n- ⚠️ Rattle **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Recommended to call Rattle functions via R script in the background (no GUI needed)\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- 💡 Suitable for data mining, decision trees, clustering, association rules\n\n**Pure CLI alternative (R script)**:\n```r\nlibrary(rattle)\n# Load data\naudit <- read.csv(\"audit.csv\")\n# Build model\nmodel <- Target ~ Age + Employment + ... \n# Output results\nsummary(model)\n```\n\n📋 Recommended usage:\n rattle --cli # try CLI mode (may still pop up, not guaranteed)\n Rscript script.R # R script calling Rattle functions (recommended, no GUI)\n\n---\n\n## OpenBUGS\n\n- ⚠️ OpenBUGS **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Can be called in the background via R packages `R2OpenBUGS` or `BRugs` (no GUI needed)\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- 💡 Suitable for Bayesian analysis, MCMC, hierarchical models\n\n**Pure CLI alternative (R script)**:\n```r\nlibrary(BRugs)\n# Define model\nmodelCheck(\"model.txt\")\nmodelData(\"data.txt\")\nmodelCompile()\nmodelUpdate(1000)\n# Extract results\nsamplesStats(\"*\")\n```\n\n📋 Recommended usage:\n openbugs --help # GUI mode\n Rscript openbugs_script.R # R script call (recommended, no GUI)\n\n---\n\n## LIMDEP\n\n- ✅ LIMDEP is a pure CLI tool, completely GUI-free, no splash screen\n- 🔴 Windows only\n- ⚠️ License file required\n- 💡 Suitable for Logit, Probit, Tobit, sample selection, Count models, Frontier analysis\n\n📋 Recommended usage (Windows):\n limdep commands.txt\n\n**English Memory Template**:\n```\n- **Version**: LIMDEP 11.0\n- **Path**: `[LIMDEP_install_PATH]\\limdep.exe`\n- **Batch Command Format**:\n ```batch\n limdep commands.txt\n ```\n- **Notes**: Windows only, license required\n```\n\n---\n\n## NLOGIT\n\n- ✅ NLOGIT is a pure CLI tool, completely GUI-free, no splash screen\n- 🔴 Windows only\n- ⚠️ License file required (included in LIMDEP license)\n- 💡 Suitable for Multinomial Logit, Nested Logit, Mixed Logit, Probit models\n\n📋 Recommended usage (Windows):\n nlogit commands.txt\n\n---\n\n## Microfit\n\n- ✅ Microfit is a pure CLI tool, completely GUI-free, no splash screen\n- 🔴 Windows only\n- ⚠️ License file required\n- 💡 Suitable for time series, econometrics, unit-root tests, ARDL, panel data\n\n📋 Recommended usage (Windows):\n microfit commands.txt\n\n---\n\n## CmdStan\n\n- ✅ CmdStan is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- ⚠️ First use requires compiling the model (time-consuming)\n- ⚠️ Requires a C++ compiler (Windows: Rtools or Visual Studio)\n- 💡 Suitable for Bayesian statistics, hierarchical models, consumer behavior modeling\n\n📋 Recommended usage:\n # Compile model\n stanc model.stan\n # Run sampling\n sample num_samples=1000 num_warmup=500 data file=data.json\n # View results\n stansummary output.csv\n\n💡 Via cmdstanr/cmdstanpy (recommended):\n Rscript -e \"library(cmdstanr); model <- cmdstan_model('model.stan'); fit <- model\\$sample(data_file='data.json')\"\n\n---\n\n## Weka\n\n- ✅ Weka is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- ⚠️ Requires Java environment (JVM)\n- ⚠️ Increase JVM memory for large data: `java -Xmx4g -jar weka.jar ...`\n- 💡 Suitable for clustering, classification, association rules, feature selection, market basket analysis\n\n📋 Recommended usage:\n # Command line classification\n java -cp weka.jar weka.classifiers.trees.RandomForest -t data.arff -T test.arff\n # Clustering\n java -cp weka.jar weka.clusterers.SimpleKMeans -t data.arff -N 3\n # Association rules\n java -cp weka.jar weka.associations.Apriori -t data.arff\n\n---\n\n## KNIME\n\n- ✅ KNIME supports headless mode, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- ⚠️ Headless mode requires installing the KNIME headless extension\n- ⚠️ Workflows must be designed in the GUI beforehand\n- 💡 Suitable for automated workflows, ETL, data mining, visual analytics\n\n📋 Recommended usage:\n # Headless workflow execution\n knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowDir=\"/path/to/workflow\"\n # Execute with parameters\n knime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION -workflowDir=\"/path/to/workflow\" -workflow.variable=myVar,value,String\n\n---\n\n## jamovi\n\n- ⚠️ jamovi **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Can call jamovi analysis modules in the background via the `jmv` R package (no GUI needed)\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- 💡 Suitable for descriptive statistics, Bayesian analysis, frequency analysis\n\n**Pure CLI alternative (R script)**:\n```r\nlibrary(jmv)\n# Descriptive statistics\ndescriptives <- jmv::descriptives(data = mydata, vars = c(\"var1\", \"var2\"))\n# Chi-square test\nchisq <- jmv::contTables(data = mydata, rows = \"group\", cols = \"outcome\")\n```\n\n📋 Recommended approach:\n Rscript jmv_script.R # R script calling jmv package (recommended, no GUI)\n\n---\n\n## JASP\n\n- ⚠️ JASP **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Can call JASP analysis modules in the background via the `jaspTools` R package (no GUI needed)\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free\n- 💡 Suitable for descriptive statistics, Bayesian analysis, exploratory analysis\n\n**Pure CLI alternative (R script)**:\n```r\nlibrary(jaspTools)\n# Load JASP data\ndata <- jaspTools::readOSR(\"data.csv\")\n# Descriptive statistics\ndesc <- jaspTools::descriptives(data, variables = c(\"var1\", \"var2\"))\n```\n\n📋 Recommended approach:\n Rscript jasp_script.R # R script calling jaspTools package (recommended, no GUI)\n\n---\n\n## PSPP\n\n- ✅ PSPP is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- ✅ Open source and free (SPSS alternative)\n- ⚠️ Syntax compatible with SPSS, but some advanced features unsupported\n- 💡 Suitable for descriptive statistics, regression, contingency tables, data cleaning\n\n📋 Recommended usage:\n # Run .sps syntax\n pspp -o output.txt analysis.sps\n # Pipe mode\n pspp < analysis.sps\n # Output directly to file\n pspp analysis.sps -o output.html\n\n---\n\n## Mplus\n\n- ✅ Mplus is a pure CLI tool, completely GUI-free, no splash screen\n- ✅ Supports Windows and Mac\n- ⚠️ License file required\n- ⚠️ Syntax is distinctive, steep learning curve\n- 💡 Suitable for SEM, latent class analysis (LCA/LPA), multilevel models, survival analysis\n\n📋 Recommended usage:\n mplus model.inp\n # With output file\n mplus model.inp output.out\n\n---\n\n## AMOS\n\n- ⚠️ AMOS **has no pure CLI mode**; invocation pops up the GUI (unavoidable)\n- ✅ Can be called in the background via the IBM SPSS Amos Python extension (no GUI needed)\n- 🔴 Windows only\n- ⚠️ Requires SPSS Statistics license\n- 💡 Suitable for SEM, path analysis, confirmatory factor analysis\n\n**Background automation (write your own, outside this skill's automation scope)**:\n- For background automation, use the official IBM SPSS Amos Python extension on your own (this skill does not drive it)\n- This skill only provides **detection + manual GUI-launch guidance** (GUI-only, no automation)\n\n📋 Recommended approach:\n # Manually launch GUI to open file (pops up, no automation)\n amos.exe model.amw\n\n---\n\n## Q (MRKS)\n\n- ✅ Q (MRKS) supports QScript batch mode, completely GUI-free, no splash screen\n- 🔴 Windows only\n- ⚠️ Requires Q (MRKS) license\n- 💡 Suitable for market-research questionnaire analysis, cross-tabs, statistical tests\n\n📋 Recommended usage (Windows):\n REM Run QScript\n Q.exe /QScript \"c:\\scripts\\analysis.qs\"\n REM With log\n Q.exe /QScript \"c:\\scripts\\analysis.qs\" /Log \"c:\\logs\\output.log\"\n\n---\n\n## NCSS\n\n```\n✅ NCSS connection configuration complete!\n\n📊 Configuration Information:\n - NCSS Version: [2024]\n - NCSS Executable: [NCSS.exe path]\n - Platform: Windows\n\n⚠️ Important notes:\n 1. NCSS supports batch mode via /B parameter\n 2. Windows-only, no macOS/Linux support\n 3. Suitable for medical statistics, sample size calculation, clinical data analysis\n\n📋 Recommended usage:\n \"NCSS.exe\" /B \"analysis.ncss\"\n```\n\n---\n\n## Origin (OriginLab)\n\n```\n✅ Origin connection configuration complete!\n\n📊 Configuration Information:\n - Origin Version: [2025/2024/2023]\n - Origin Executable: [Origin95.exe or Origin97.exe path]\n - Platform: Windows\n\n⚠️ Important notes:\n 1. Origin supports LabTalk script batch processing via -h parameter\n 2. Scientific graphing and data analysis software, over 1M users worldwide\n 3. macOS CLI support is limited, Windows environment recommended\n 4. Suitable for batch data processing, scientific figure generation, statistical analysis\n\n📋 Recommended usage:\n \"origin97.exe\" -h \"script.ogs\"\n```\n\n---\n\n## Generic Memory Template Format\n\nIf the software is not listed in this document, use the following generic template:\n\n**English Memory Template**:\n```\n### [Software] Environment\n\n- **Version**: [version]\n- **Executable Path**: `[path]`\n- **Batch Command Format**:\n ```bash\n [command]\n ```\n- **Script Template**:\n ```[language]\n [code]\n ```\n- **Common Errors & Solutions**:\n | Error | Cause | Solution |\n |-------|-------|---------|\n | [error1] | [cause] | [solution] |\n- **Configuration Completion Notes**:\n - ✅ [benefit1]\n - ⚠️ [caution1]\n```\n\nFile v2.8.2:references/config-templates.md\n\n# Configuration & Memory Templates\n\n## SPSS Statistics Memory Template\n\n```markdown\n### SPSS Statistics Environment\n\n- **Version**: IBM SPSS Statistics [26/27/28/29/30/31]\n- **Main Executable**: `C:\\Program Files\\IBM\\SPSS\\Statistics\\[version]\\stats.exe`\n- **Invocation Priority**:\n 1. **Approach 1 (preferred)**: `stats.com` console version + `.spj` file → completely splash-free, **foolproof**\n ```bash\n \"C:\\Program Files\\IBM\\SPSS\\Statistics\\[version]\\stats.com\" -production silent -nologo \"job.spj\"\n ```\n 2. **Approach 2 (fallback)**: internal Python driver `spss.Submit()` → splash-free, **but can only run pure analysis syntax**\n - ❌ Must not contain `OUTPUT SAVE`, `OUTPUT EXPORT`, `HOST COMMAND`, `XDATA`, etc.\n 3. **Approach 3 (last resort)**: `stats.exe` GUI version + `.spj` → may show a splash screen\n ```bash\n \"C:\\Program Files\\IBM\\SPSS\\Statistics\\[version]\\stats.exe\" -production silent -nologo \"job.spj\"\n ```\n- **Built-in Python path**: `C:\\Program Files\\IBM\\SPSS\\Statistics\\[version]\\Python3\\python.exe`\n- **.spj file XML structure template**:\n ```xml\n \n \n \n \n \n \n ```\n```\n\n## SPSS Statistics Version Differences\n\n### Python Version Comparison\n\n| SPSS Statistics Version | Bundled Python | f-string Support |\n|-------------------------|---------------|-----------------|\n| 26 | Python 3.4 | ❌ |\n| 27 | Python 3.8 | ✅ |\n| 28 | Python 3.9 | ✅ |\n| 29 | Python 3.10.4 | ✅ |\n| 30 | Python 3.10 | ✅ |\n\n### spss_helper.py Compatibility\n\n- SPSS Statistics 26: Script uses `%s` / `.format()`, no f-string\n- SPSS Statistics 27+: Script can use f-string and modern Python\n\n## SPSS Modeler Memory Template\n\n```markdown\n### SPSS Modeler Environment\n\n- **Version**: IBM SPSS Modeler [18.0/18.1/18.2/18.3/18.4/18.5/18.6]\n- **Main Executable**: `C:\\Program Files\\IBM\\SPSS\\Modeler\\[version]\\bin\\clemb.exe`\n- **modelerclient.exe**: `C:\\Program Files\\IBM\\SPSS\\Modeler\\[version]\\bin\\modelerclient.exe`\n- **Batch Mode command format**:\n ```powershell\n # Run stream file\n clemb.exe -local -stream \"job.str\" -log \"output.log\" -execute\n\n # Run Python script (recommended)\n clemb.exe -local -script \"train_model.py\" -scriptlang python -log \"train.log\" -execute\n ```\n- **Config Field**: `config.json > \"SPSS Modeler\"`\n- **Difference from Statistics**: Statistics is a statistical analysis tool, Modeler is a data mining/modeling tool\n```\n\n## SPSSModeler Version Differences\n\n| Version | clemb.exe Path | Notes |\n|---------|---------------|-------|\n| 18.6 | `C:\\Program Files\\IBM\\SPSS\\Modeler\\18.6\\bin\\clemb.exe` | Latest, Python scripting |\n| 18.5 | `C:\\Program Files\\IBM\\SPSS\\Modeler\\18.5\\bin\\clemb.exe` | Performance improvements |\n| 18.0 | `C:\\Program Files\\IBM\\SPSS\\Modeler\\18.0\\bin\\clemb.exe` | Classic stable |\n\n## Stata Memory Template\n\n```markdown\n### Stata Environment\n\n- **Version**: Stata [VERSION] [EDITION] (MP/SE/BE)\n- **Main Executable Path**: `[STATA_EXE_PATH]` (e.g., `StataMP-64.exe`)\n- **Batch Command Format**:\n ```bash\n # Windows — new MP/SE (Stata 14+)\n \"[STATA_EXE_PATH]\" /b do \"script.do\"\n # Windows — old SE (e.g., Stata 12 SE) use /e to avoid popup\n \"[STATA_EXE_PATH]\" /e do \"script.do\"\n ```\n```\n\n## Stata Version Differences\n\n| Edition | License Match | Notes |\n|---------|--------------|-------|\n| MP (Multiprocessing) | ✅ Multi-core | Best for large data |\n| SE (Special Edition) | ✅ Single-core | Mid-size data |\n| BE (Basic Edition) | ✅ Limited | No parallelism |\n\n## R Memory Template\n\n```markdown\n### R Environment\n\n- **Version**: R [VERSION]\n- **Rscript Path**: `[RSCRIPT_EXE_PATH]`\n- **Batch Command Format**:\n ```bash\n Rscript --vanilla \"script.R\"\n ```\n```\n\n## SAS Memory Template\n\n```markdown\n### SAS Environment\n\n- **Version**: SAS [VERSION] (e.g., 9.4)\n- **Executable Path**: `[SAS_EXE_PATH]`\n```\n\n## Minitab Memory Template\n\n```markdown\n### Minitab Environment\n\n- **Version**: Minitab [22/21/20/19/18]\n- **Main Executable**: `C:\\Program Files\\Minitab\\Minitab [VERSION]\\mtb.exe`\n- **Automation**: ❌ **GUI-only** — `mtb.exe /run \"script.mtb\"` opens the Minitab GUI window and is not headless-safe; never call it from the agent. Detect the install and let the user run analyses interactively (or via Minitab Web App).\n- **Config Field**: `config.json > \"Minitab\"`\n- **macOS / Linux**: No native CLI; use Minitab Web App (https://app.minitab.com/) or remote desktop to a Windows host\n```\n\n## R — Alternative when R is not available\n\n| R Package | Anaconda Python Alternative |\n|-----------|---------------------------|\n| dplyr / tidyr | pandas |\n| ggplot2 | matplotlib / seaborn |\n| caret / xgboost | scikit-learn |\n| survival | lifelines |\n| lme4 / nlme | statsmodels |\n\n## Configuration File (config.json)\n\n```json\n{\n \"platform\": \"windows\",\n \"R\": { \"installed\": true, \"path\": \"C:\\\\Program Files\\\\R\\\\R-4.5.1\\\\bin\\\\Rscript.exe\", \"version\": \"4.5.1\", \"mode\": \"simple\" },\n \"Stata\": { \"installed\": true, \"path\": \"C:\\\\Program Files\\\\Stata17\\\\StataMP-64.exe\", \"edition\": \"MP\", \"version\": \"17\", \"mode\": \"simple\" },\n \"SAS\": { \"installed\": true, \"path\": \"C:\\\\Program Files\\\\SASFoundation\\\\9.4\\\\sas.exe\", \"version\": \"9.4\", \"mode\": \"simple\" },\n \"SPSS\": { \"installed\": true, \"version\": \"28\", \"path\": \"C:\\\\Program Files\\\\IBM\\\\SPSS\\\\Statistics\\\\28\\\\stats.exe\", \"mode\": \"simple\" }\n}\n```\n\n## Common Errors & Solutions\n\n| Software | Error | Cause | Solution |\n|----------|-------|-------|----------|\n| SPSS | NullPointerException | .spj missing `` | Add complete XML |\n| SPSS | UnicodeDecodeError | Non-UTF-8 output | Use `cp1252` or `errors='replace'` |\n| SPSS | K=1 result | High variable dimensionality | Reduce noise variables |\n| SPSS | F-string error | Python 3.4 limitation | Use `%s` formatting |\n| Stata | Confirmation dialog | Wrong batch flag | Stata ≤12: `/e` (Win) or `-e` (Mac/Linux); Stata ≥13: `/b` (Win) or `-b` (Mac/Linux) |\n| Stata | File not found | Spaces in path | Wrap path in quotes |\n| R | Package not found | Package not installed | `install.packages()` |\n| R | Encoding issue | Non-UTF-8 file | Use `fileEncoding=\"UTF-8\"` |\n| SAS | License expired | Expired license | Update license file |\n| SAS | Encoding issue | Encoding mismatch | `options encoding='utf-8';` |\n\n## Completion Prompt Templates\n\n### SPSS (preferred success)\n\n```\n✅ SPSS [version] configuration complete!\n\n📋 Configuration:\n - Version: IBM SPSS Statistics [version]\n - Path: [install_path]\n - Bundled Python: [python_path] (Python [ver])\n - f-string: [✅/❌]\n\n✅ Internal Python test passed (no splash screen).\n```\n\n### Stata\n\n```\n✅ Stata [version] configuration complete!\n\n⚠️ Notes:\n 1. New MP/SE (14+) use `/b`; old SE (e.g., Stata 12) must use `/e`\n 2. Wrap paths with spaces in quotes\n 3. License match: MP→StataMP-64.exe / SE→StataSE-64.exe / BE→Stata-64.exe\n\n📋 Invocation:\n \"StataMP-64.exe\" /b do \"script.do\"\n```\n\n### R\n\n```\n✅ R [version] configuration complete!\n\n⚠️ Notes:\n 1. Use Rscript --vanilla, not GUI\n 2. Use fileEncoding=\"UTF-8\" for Chinese encoding\n 3. Use data.table/arrow for large memory data\n\n📋 Invocation:\n \"[Rpath]\\Rscript.exe\" --vanilla \"script.R\"\n```\n\n### SAS\n\n```\n✅ SAS [version] configuration complete!\n\n⚠️ Notes:\n 1. Batch mode generates .log and .lst files\n 2. Use options encoding='utf-8'; for Chinese\n 3. Ensure license is not expired\n\n📋 Invocation:\n sas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"\n```\n\n## Platform-Specific Paths\n\n### R\n- Windows: `C:\\Program Files\\R\\`\n- Mac: `/Library/Frameworks/R.framework/`\n- Linux: `/usr/lib/R/`\n\n### Stata\n- Windows: `C:\\Program Files\\Stata17\\`; `C:\\Program Files\\Stata18\\`\n- Mac: `/Applications/Stata/`\n- Linux: `/usr/local/stata/`\n\n### SPSS (Windows only)\n`C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\` → `31`\n\n### JMP (Windows only)\n`C:\\Program Files\\JMP\\16\\`; `\\17\\`\n\n### GraphPad (Windows only)\n`C:\\Program Files\\GraphPad\\Prism 9\\`; `\\10\\`\n\n## Advanced Mode Scripts\n\n| Software | Windows Command |\n|----------|-----------------|\n| R | `statsoft-r run script.R` |\n| SAS | `statsoft-sas run program.sas` |\n| SPSS | `statsoft-spss run syntax.sps` |\n| SPSS (batch) | `statsoft-spss run-batch s1.sps s2.sps s3.sps` |\n| JMP (Windows, CLI) | `statsoft-jmp run script.jsl` — only executes user-provided JSL scripts, requires explicit user confirmation |\n\nFile v2.8.2:references/platform-support.md\n\n# Platform Support\n\n## Full Matrix\n\n| Category | Software | Notes |\n|----------|----------|-------|\n| ✅ All platforms (Win + Mac + Linux, CLI) | R, Stata, SAS, CmdStan, GenStat, Gretl, H2O.ai, JAGS, Julia, KNIME, Mathematica, Matlab, OpenBUGS, Orange, OxMetrics, PSPP, Rattle, SHAZAM, Stat/Transfer, Tanagra, TSP, Weka | Full CLI automation on all platforms |\n| ✅ Win + Mac + Limited Linux | Mplus | Limited Linux support |\n| ⚠️ Win + Limited Mac/Linux | Minitab | Limited Mac/Linux |\n| 🔴 Windows only | SPSS Statistics, EViews, JMP, LIMDEP, Microfit, NCSS, NLOGIT, Origin, Q (MRKS), SPSS Modeler, Statistica | Windows-only CLI |\n| 🔴 GUI-only (detection + manual-launch only) | AMOS, GraphPad Prism, JASP, jamovi | Can detect and guide manual GUI launch; no CLI batch automation |\n\n## GUI-Only Software\n\nGUI-only software (AMOS, GraphPad Prism, JASP, jamovi) is limited to **detection + manual-launch guidance** — this skill never drives them via CLI/headless automation, and never creates or modifies their project/data files (including GraphPad Prism `.pzfx`).\n\n## Version-Specific Notes\n\nSee `version-specifics.md` for version differences (SPSS 26/30, R 4.5/4.1, Python 3.4/3.13).\n\nFile v2.8.2:references/trust-and-safety.md\n\n# Trust & Safety\n\nThis skill performs **high-risk operations**. Understand risk levels before use:\n\n| Risk | Level | Description |\n|------|-------|-------------|\n| Execute local executables | 🔴 High | Launches detected statistical software (e.g., `stats.exe`, `Rscript.exe`) |\n| Download & install software | 🔴 High | Fetches R installer from CRAN, Anaconda installer from Anaconda repos |\n| Modify config.json | 🟡 Medium | Writes software paths, backs up existing config |\n| Execute user-provided scripts | 🔴 High | Runs `.sps` content via SPSS Python, creating temporary wrapper scripts |\n| Network access | 🟡 Medium | Downloads installers from CRAN, Anaconda repositories |\n\n> Required permissions (local file read/write / process execution / network access) are described in the \"Core Permissions\" section of `SKILL.md`.\n\n**Pre-flight**: ✅ Review all scripts; ✅ Confirm config.json changes (auto-backed up); ✅ Confirm any download tasks; ✅ Check generated commands for sensitive projects.\n\nFile v2.8.2:references/version-specifics.md\n\n# Version & Platform Specifics\n\n> Reference for version differences across statistical software.\n\n---\n\n## Platform Support Summary\n\n| Software | Windows | macOS | Linux |\n|----------|---------|-------|-------|\n| R | ✅ | ✅ | ✅ |\n| Stata | ✅ | ✅ | ✅ |\n| SAS | ✅ | ✅ | ✅ |\n| StatTransfer | ✅ | ✅ | ❌ |\n| Gretl | ✅ | ✅ | ✅ |\n| Matlab | ✅ | ✅ | ✅ |\n| Mathematica | ✅ | ✅ | ✅ |\n| Julia | ✅ | ✅ | ✅ |\n| Minitab | ✅ | ⚠️ | ⚠️ |\n| SPSS Statistics | ✅ | ❌ | ❌ |\n| SPSS Modeler | ✅ | ❌ | ❌ |\n| JMP | ✅ | ⚠️ | ⚠️ |\n| GraphPad Prism | ✅ | ❌ | ❌ |\n| EViews | ✅ | ❌ | ❌ |\n| Statistica | ✅ | ❌ | ❌ |\n| CmdStan | ✅ | ✅ | ✅ |\n| Weka | ✅ | ✅ | ✅ |\n| KNIME | ✅ | ✅ | ✅ |\n| jamovi | ✅ | ✅ | ✅ |\n| JASP | ✅ | ✅ | ✅ |\n| PSPP | ✅ | ✅ | ✅ |\n| Mplus | ✅ | ✅ | ❌ |\n| AMOS (IBM) | ✅ | ❌ | ❌ |\n| Q / MRKS | ✅ | ❌ | ❌ |\n| JAGS | ✅ | ✅ | ✅ |\n| SHAZAM | ✅ | ✅ | ✅ |\n| OxMetrics | ✅ | ✅ | ✅ |\n| TSP | ✅ | ✅ | ✅ |\n| Tanagra | ✅ | ✅ | ✅ |\n| Orange | ✅ | ✅ | ✅ |\n| H2O.ai | ✅ | ✅ | ✅ |\n| GenStat | ✅ | ✅ | ✅ |\n| Rattle | ✅ | ✅ | ✅ |\n| OpenBUGS | ✅ | ✅ | ✅ |\n| LIMDEP | ✅ | ❌ | ❌ |\n| NLOGIT | ✅ | ❌ | ❌ |\n| Microfit | ✅ | ❌ | ❌ |\n\n---\n\n## SPSS Statistics Version Differences\n\n| Version | Bundled Python | f-string Support |\n|---------|---------------|-----------------|\n| 26 | Python 3.4 | ❌ |\n| 27 | Python 3.8 | ✅ |\n| 28 | Python 3.9 | ✅ |\n| 29 | Python 3.10.4 | ✅ |\n| 30 | Python 3.10 | ✅ |\n\n### spss_helper.py Compatibility\n\n- SPSS Statistics 26: Script uses `%s` / `.format()`, no f-string\n- SPSS Statistics 27+: Script can use f-string and modern Python\n\n---\n\n## SPSS Modeler Version Differences\n\n| Version | clemb.exe Path | Notes |\n|---------|---------------|-------|\n| 18.6 | `...\\Modeler\\18.6\\bin\\clemb.exe` | Latest, Python scripting |\n| 18.5 | `...\\Modeler\\18.5\\bin\\clemb.exe` | Performance improvements |\n| 18.0 | `...\\Modeler\\18.0\\bin\\clemb.exe` | Classic stable |\n\n### clemb.exe Common Arguments\n\n```\n-local Run in local mode (batch recommended)\n-stream Load and execute .str stream file\n-script Load and execute Python script\n-project Load project\n-execute Execute loaded stream/script\n-log Redirect log to file\n-server Server mode (requires Modeler Server)\n-hostname Server address\n-port Server port\n-username Username\n-password

Password\n```\n\n---\n\n## CmdStan Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 2.30+ | Latest, improved threading, pathfinder |\n| 2.28+ | Improved HMC adaptation |\n| 2.26+ | Generated quantities redesign |\n\n### CmdStan CLI Usage\n\n```bash\n# Compile model\ncd $CMDSTAN && make /path/to/model\n\n# Run sampling\n./model sample num_samples=2000 num_warmup=1000 data file=init.csv output file=out.csv\n\n# Summary\nstansummary out.csv\n```\n\n---\n\n## Weka CLI Usage\n\n```bash\n# Run filter/from command line\njava -cp $WEKA_HOME/weka.jar weka.filters.unsupervised.attribute.StringToWVector \\\n -i input.arff -o output.arff\n\n# Classifier\njava -cp $WEKA_HOME/weka.jar weka.classifiers.trees.RandomForest \\\n -t train.arff -T test.arff -p 0\n```\n\n---\n\n## KNIME Batch Usage\n\n```bash\n# Headless batch mode\nknime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION \\\n -workflowFile=/path/to/workflow.knwf \\\n -workflow.variable=threshold,0.5,double\n\n# CLI only (KNIME Server)\nknime -nosplash -application org.knime.product.KNIME_BATCH_APPLICATION \\\n -workflowDir=/path/to/workflow_directory\n```\n\n---\n\n## Mplus Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 8.11 | Latest (2025) |\n| 8.10 | BCH method for mixture models |\n| 8.8 | Improved multilevel |\n| 8.0 | Baseline |\n\n### Mplus CLI Usage\n\n```bash\n# Batch mode — create .inp file with DATA/FILEDATA/SAVEDATA/OUTPUT\n# Then:\nmplus model.inp\n\n# Example .inp file:\nTITLE: My analysis\nFILEDATA: FILE IS data.dat;\nMODEL: y ON x1 x2;\nOUTPUT: MODINDICES STANDARDIZED;\nSAVEDATA: FILE IS results.dat;\n```\n\n---\n\n## Stata Version Differences\n\n| Version | Windows Batch Flag | Mac/Linux Batch Flag |\n|---------|-------------------|---------------------|\n| ≤ 12 | `/e do \"script.do\"` | `-e do \"script.do\"` |\n| ≥ 13 | `/b do \"script.do\"` | `-b do \"script.do\"` |\n\n---\n\n## R Version Differences\n\n| R Version | Bundled Python | SPSS Equivalent |\n|-----------|---------------|-----------------|\n| 3.4 | Python 3.4 | SPSS Statistics 26 |\n| 3.5+ | Python 3.7+ | SPSS Statistics 27+ |\n| 4.0+ | Python 3.9+ | SPSS Statistics 30+ |\n\n---\n\n## SAS Version Differences\n\n| Platform | Batch Mode |\n|----------|-----------|\n| Windows | `sas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"` |\n| Linux | `sas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"` |\n| macOS | `sas -sysin \"prog.sas\" -log \"out.log\" -print \"out.lst\"` |\n\n---\n\n## JMP Version Differences\n\n| Version | Extension | Batch Command |\n|---------|-----------|--------------|\n| 14/15/16 | `.jsl` | `JMP.exe /R \"script.jsl\"` |\n| 16 Pro | `.jsl` | `JMP.exe /S /R \"script.jsl\"` |\n| JMP Live | Web-based | Web API |\n\n---\n\n## jamovi Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 2.4+ | Latest, Rj module support |\n| 2.3+ | Improved syntax export |\n\n### jamovi Execution\n\n> ⚠️ jamovi has **no pure CLI mode** and cannot run silently/batch. This skill provides detection and manual GUI-launch guidance only (GUI-only).\n\n**Alternative (R script, no GUI)**: Use the `jmv` R package to run jamovi modules in the background:\n```r\nlibrary(jmv)\ndescriptives <- jmv::descriptives(data = mydata, vars = c(\"var1\", \"var2\"))\n```\n\n---\n\n## JASP Version Differences\n\n| Version | Notes | CLI Status |\n|---------|-------|-----------|\n| 0.18+ | Latest | ⚠️ No stable CLI (GUI-only) |\n| 0.16+ | Improved modules | ⚠️ Limited CLI |\n\n### JASP Execution\n\n> ⚠️ JASP has **no pure CLI mode** and cannot run silently/batch. This skill provides detection and manual GUI-launch guidance only (GUI-only).\n\n> This skill does NOT automate JASP via R/jaspTools in the background — JASP is GUI-only; detection + manual-launch guidance only.\n\n---\n\n## PSPP Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 2.0+ | Latest, improved compatibility |\n| 1.6+ | Added GLM |\n\n### PSPP CLI Usage\n\n```bash\n# Run .sps syntax\npspp -o output.txt analysis.sps\n\n# Pipe mode\npspp < analysis.sps\n```\n\n---\n\n## AMOS Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 29.0 | Latest (SPSS Statistics 29 bundle) |\n| 28.0 | Improved multi-group |\n| 27.0 | Baseline |\n\n### AMOS Execution\n\n> ⚠️ AMOS has **no CLI mode** and cannot run silently/batch. This skill provides detection and manual GUI-launch guidance only (GUI-only).\n\n> AMOS is GUI-only; this skill provides NO background automation (including any script shown in reference docs). For automation, the user must write it themselves outside this skill's scope.\n\n---\n\n## Q (MRKS) Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 6.0+ | Latest |\n| 5.5+ | Improved R integration |\n\n### Q Batch Usage\n\n```batch\nREM Run QScript\nQ.exe /QScript \"c:\\scripts\\analysis.qs\"\n```\n\n---\n\n## Mathematica Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 14.0 | Latest (2024), improved WolframScript |\n| 13.0 | Baseline for modern Wolfram Language |\n| 12.0 | First version with full WolframScript support |\n\n### Mathematica CLI Usage\n\n```bash\n# Run Wolfram Language script\nwolframscript -file script.wl\n\n# Execute code directly\nwolframscript -code \"Table[i^2, {i, 10}]\"\n\n# Windows explicit MathKernel call\n\"C:\\Program Files\\Wolfram Research\\Mathematica\\14.0\\MathKernel.exe\" -noprompt < script.m\n```\n\n### Mathematica Common Errors\n\n| Error | Solution |\n|-------|----------|\n| `wolframscript not found` | Add Mathematica to PATH or use full path |\n| License activation required | Run Mathematica GUI once to activate |\n| `MathKernel` hangs | Use `-noprompt` flag for batch mode |\n\n---\n\n## Common Errors & Solutions\n\n| Software | Error | Solution |\n|----------|-------|----------|\n| SPSS Statistics | NullPointerException | Add `` to .spj XML |\n| SPSS Statistics | UnicodeDecodeError | Use `cp1252` or `errors='replace'` |\n| SPSS Statistics | F-string error (v26) | Use `%s` formatting |\n| SPSS Modeler | Stream not found | Verify file path and .str extension |\n| CmdStan | `stanc` not found | Set CMDSTAN env var, run setup |\n| CmdStan | Compilation fails | Check C++ toolchain |\n| Weka | Out of memory | Use `-Xmx` JVM flag with Java |\n| KNIME | `-workflowDir` not recognized | Update to KNIME 4.7+ |\n| Mplus | License not found | Check license file |\n| Mplus | Model not found | Verify .inp file and data path |\n| Stata | Confirmation dialog | Loop: v≤12 → `/e`, v≥13 → `/b` |\n| R | Package not installed | `install.packages()` |\n| SAS | License expired | Update license file |\n\n---\n\n## JAGS Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 4.3.0 | Latest stable |\n| 4.2.0 | Improved parallel chain support |\n\n### JAGS CLI Usage\n\n```bash\n# Run JAGS script\njags scriptfile\n\n# Batch execution\njags-script script.txt\n\n# With R interface\nRscript -e \"library(rjags); jags.model('script.dat', data)\"\n```\n\n### JAGS Common Errors\n\n| Error | Solution |\n|-------|----------|\n| `Cannot find JAGS` | Install JAGS |\n| Syntax error in model | Check BUGS syntax |\n| MCMC did not converge | Increase burn-in and iterations |\n\n---\n\n## SHAZAM Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 12.0 | Latest, improved command language |\n| 11.0 | Baseline |\n\n### SHAZAM CLI Usage\n\n```bash\n# Run SHAZAM command file\nshazam commands.txt\n\n# Sample command file content:\n# /MODEL TITLE MYMODEL\n# / X 1 100\n# / PREDICT Y\n# /END\n```\n\n---\n\n## OxMetrics Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 8.0 | Latest (Ox 8) |\n| 7.0 | Baseline |\n\n### OxMetrics CLI Usage\n\n```bash\n# Show CLI options\noxmetrics --help\n\n# Run batch\noxmetrics -b commands.txt\n```\n\n---\n\n## TSP Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 5.0 | Latest |\n| 4.5 | Baseline |\n\n### TSP CLI Usage\n\n```bash\n# Run TSP command file\ntsp commands.txt\n```\n\n---\n\n## Tanagra Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 1.8 | Latest |\n| 1.5 | Baseline |\n\n### Tanagra CLI Usage\n\n```bash\n# Show CLI options\ntanagra --help\n\n# Execute batch script\ntanagra -f script.txt\n```\n\n---\n\n## Orange Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 3.36 | Latest |\n| 3.30 | Baseline |\n\n### Orange CLI Usage\n\n```bash\n# Show CLI options (GUI mode)\norange-canvas --help\n\n# Python module approach (recommended)\npython3 -m Orange.canvas\n```\n\n### Orange Common Errors\n\n| Error | Solution |\n|-------|----------|\n| Module not found | `pip install orange3` |\n| Conda issues | `conda install -c condaforge orange3` |\n\n---\n\n## H2O.ai Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 3.44 | Latest |\n| 3.40 | AutoML improvements |\n\n### H2O CLI Usage\n\n```bash\n# Show CLI options\nh2o --help\n\n# Start H2O server\nh2o start\n\n# Via Python (recommended)\npython3 -c \"import h2o; h2o.init()\"\n```\n\n### H2O Common Errors\n\n| Error | Solution |\n|-------|----------|\n| Server not starting | Check Java, `java -version` |\n| Out of memory | Set `-Xmx` in `h2o.start()` |\n| Port conflict | Change port: `h2o.init(port=54322)` |\n\n---\n\n## GenStat Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 23.0 | Latest |\n| 22.0 | Baseline |\n\n### GenStat CLI Usage\n\n```bash\n# Show CLI options\ngenstat --help\n\n# Run GenStat command file\ngenstat commands.txt\n```\n\n---\n\n## Rattle Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 5.5 | Latest |\n| 5.0 | Baseline |\n\n### Rattle CLI Usage\n\n```bash\n# Run Rattle in CLI mode\nrattle --cli\n\n# Via R package\nRscript -e \"library(rattle); rattle()\"\n```\n\n---\n\n## OpenBUGS Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 3.2.3 | Latest stable |\n| 3.2.2 | Baseline |\n\n### OpenBUGS CLI Usage\n\n```bash\n# Show CLI options\nopenbugs --help\n\n# Batch execution via script\nopenbugs -b script.txt\n```\n\n---\n\n## LIMDEP Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 11.0 | Latest |\n| 10.0 | Baseline |\n\n### LIMDEP CLI Usage\n\n```batch\nREM Run LIMDEP command file\nlimdep commands.txt\n```\n\n### LIMDEP Common Errors\n\n| Error | Solution |\n|-------|----------|\n| License not found | Check license file |\n| Data not found | Verify data path in command file |\n\n---\n\n## NLOGIT Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 6.0 | Latest |\n| 5.0 | Discrete choice improvements |\n\n### NLOGIT CLI Usage\n\n```batch\nREM Run NLOGIT command file\nnlogit commands.txt\n```\n\n### NLOGIT Common Errors\n\n| Error | Solution |\n|-------|----------|\n| Model not converging | Check starting values |\n| Sample size mismatch | Verify data dimensions |\n\n---\n\n## Microfit Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 5.0 | Latest |\n| 4.0 | Baseline |\n\n### Microfit CLI Usage\n\n```batch\nREM Run Microfit command file\nmicrofit commands.txt\n```\n\n---\n\n## NCSS\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash |\n|----------|-----------|-------------|--------|\n| Windows | ✅ | ✅ (/B parameter) | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 2024 | Latest, batch mode support |\n| 2023 | Baseline |\n\n### NCSS Invocation\n\n> ⚠️ Reference only — this skill provides detection + manual-launch guidance for NCSS and does NOT auto-execute its CLI. To run batch analysis manually:\n> `\"NCSS.exe\" /B \"analysis.ncss\"`\n\n---\n\n## Origin (OriginLab)\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash |\n|----------|-----------|-------------|--------|\n| Windows | ✅ | ✅ (-h parameter) | ❌ |\n| macOS | ✅ | ⚠️ Limited | ⚠️ May have |\n| Linux | ❌ | ❌ | — |\n\n### Version Differences\n\n| Version | Notes |\n|---------|-------|\n| 2025 | Latest, improved LabTalk support |\n| 2024 | Baseline |\n| 2023 | Older versions may have limited CLI support |\n\n### Origin Invocation\n\n> ⚠️ Reference only — this skill provides detection + manual-launch guidance for Origin and does NOT auto-execute its CLI. To run a LabTalk script manually:\n> `origin97 -h script.ogs`\n\nFile v2.8.2:references/workflow.md\n\n# Workflow Gating Detail\n\nThe full step-by-step workflow lives in `SKILL.md` (Execution Workflow). This file only supplements the per-step default-deny gating details, to avoid duplication with `SKILL.md`.\n\n## Scan Disclosure\n\nThe batch system scan (`scan_all.*`) is **skipped entirely without explicit consent** (prints a notice, exits 0, no output). With consent (set `STATSOFT_AUTO_WRITE` to `1`, or `STATSOFT_CONFIRM` to `1` plus an interactive `y`) it returns the full `{path, version}` JSON. `STATSOFT_REVEAL` governs **per-software setup** output only — it does not affect the batch scan.\n\n## Persistence Gate\n\n`config.json` is written only with explicit authorization: set `STATSOFT_AUTO_WRITE` to `1` (non-interactive / agent) or `STATSOFT_CONFIRM` to `1` plus an interactive `y`. All writes go through `scripts/common/write_config.py`:\n\n- Accepts either canonical `config.json` (skill root **or** `scripts/windows-only/`) as the target, and **mirrors the write to the other canonical location** so the two never diverge (fail-closed, dual-canonical);\n- Before writing, takes a timestamped backup `config.json.bak.yyyymmdd_hhmmss`, then atomically replaces.\n\nPersistence happens only with explicit opt-in (set `STATSOFT_AUTO_WRITE` to `1`, or `STATSOFT_CONFIRM` to `1` plus an interactive `y`). All writes go through `scripts/common/write_config.py`, which enforces a single canonical target and a timestamped backup before atomic replace.\n\n## Third-party Binaries\n\nLaunching third-party binaries solely for version/checksum verification requires `STATSOFT_VERIFY` set to `1`; compiling and running a user-supplied Stan model (untrusted native code) requires `STATSOFT_CMDSTAN_RUN` set to `1`.\n\nFile v2.8.2:ADDITIONAL_SOFTWARE.md\n\n# Additional Statistical Software Support\n\nThis file contains configuration information for additional statistical software in the `statsoft-cli` skill (core software SPSS Statistics, R, Stata, SAS see SKILL.md).\n\n---\n\n## Table of Contents\n\n0. [Script Routing Tables](#script-routing-tables)\n1. [AMOS](#amos)\n2. [CmdStan](#cmdstan)\n3. [EViews](#eviews)\n4. [GenStat](#genstat)\n5. [GraphPad Prism](#graphpad-prism)\n6. [Gretl](#gretl)\n7. [H2O.ai](#h2oai)\n8. [JAGS](#jags)\n9. [JASP](#jasp)\n10. [JMP](#jmp)\n11. [Julia](#julia)\n12. [KNIME](#knime)\n13. [LIMDEP](#limdep)\n14. [Matlab](#matlab)\n15. [Mathematica](#mathematica)\n16. [Microfit](#microfit)\n17. [Minitab](#minitab)\n18. [Mplus](#mplus)\n19. [NCSS](#ncss)\n20. [NLOGIT](#nlogit)\n21. [OpenBUGS](#openbugs)\n22. [Orange](#orange)\n23. [OriginLab Origin](#originlab-origin)\n24. [OxMetrics](#oxmetrics)\n25. [PSPP](#pspp)\n26. [Q (MRKS)](#q-mrks)\n27. [Rattle](#rattle)\n28. [SHAZAM](#shazam)\n29. [SPSS Modeler](#spss-modeler)\n30. [Stat/Transfer](#stattransfer)\n31. [Statistica](#statistica)\n32. [Tanagra](#tanagra)\n33. [TSP](#tsp)\n34. [Weka](#weka)\n35. [jamovi](#jamovi)\n\n---\n\n## Script Routing Tables\n\n> **GUI Software Note**: The following software **have no CLI mode** — they launch a GUI and cannot run fully silent. This skill provides detection and manual-launch guidance only (you open the GUI yourself); it never auto-launches GUI applications and offers no batch automation.\n> - **AMOS** — GUI only\n> - **GraphPad Prism** — GUI only\n> - **JASP** — Requires GUI\n> - **jamovi** — Requires GUI\n\n### Windows Only\n\n| Software | Configuration Script | CLI Wrapper | Verify |\n|----------|----------------------|-------------|--------|\n| AMOS | `scripts/windows-only/AMOS/setup_amos.ps1` | — | Check install |\n| EViews | `scripts/windows-only/EViews/setup_eviews.ps1` | `scripts/windows-only/EViews/statsoft-eviews.ps1` | `EViews.exe /?` |\n| GraphPad | `scripts/windows-only/GraphPad/setup_graphpad.ps1` | — (GUI-only, no CLI wrapper) | No CLI (manual GUI launch to verify) |\n| JMP | `scripts/windows-only/JMP/setup_jmp.ps1` | `scripts/windows-only/JMP/statsoft-jmp.ps1` | `JMP.exe /R \"Exit();\"` |\n| LIMDEP | `scripts/windows-only/Limdep/setup_limdep.ps1` | — | `limdep commands.txt` |\n| Mathematica | `scripts/windows-only/Mathematica/setup_mathematica.ps1` | `scripts/cross-platform/Mathematica/setup_mathematica.sh` | `wolframscript -code \"Print[1]\"` |\n| Microfit | `scripts/windows-only/Microfit/setup_microfit.ps1` | — | `microfit commands.txt` |\n| Minitab | `scripts/windows-only/Minitab/setup_minitab.ps1` | — | No CLI (manual GUI launch; `mtb.exe /run` opens GUI) |\n| Mplus | `scripts/windows-only/Mplus/setup_mplus.ps1` | — | `mplus model.inp` |\n| NCSS | `scripts/windows-only/NCSS/setup_ncss.ps1` | — | Check install |\n| NLOGIT | `scripts/windows-only/NLOGIT/setup_nlogit.ps1` | — | `nlogit commands.txt` |\n| Q (MRKS) | `scripts/windows-only/Q_MRKS/setup_q.ps1` | — | Check install |\n| SHAZAM | `scripts/windows-only/SHAZAM/setup_shazam.ps1` | — | `shazam commands.txt` |\n| SPSS Modeler | `scripts/windows-only/SPSS/setup_modeler.ps1` | — | `clemb -local -stream test.str -execute` |\n| Statistica | `scripts/windows-only/Statistica/setup_statistica.ps1` | `scripts/windows-only/Statistica/statsoft-statistica.ps1` | `Statistica.exe /?` |\n| Origin | `scripts/windows-only/Origin/setup_origin.ps1` | — | `origin97 -h test.ogs` |\n\n### Cross-Platform\n\n> **Note**: JASP and jamovi require GUI, cannot run in pure CLI silent mode.\n\n| Software | Configuration Script | CLI Wrapper | Verify |\n|----------|----------------------|-------------|--------|\n| CmdStan | — | `scripts/cross-platform/CmdStan/setup_cmdstan.sh` | Check install |\n| GenStat | — | `scripts/cross-platform/GenStat/setup_genstat.sh` | `genstat --help` |\n| Gretl | — | `scripts/cross-platform/Gretl/setup_gretl.sh` | `gretlcli -v` |\n| H2O.ai | — | `scripts/cross-platform/H2O/setup_h2o.sh` | `h2o --help` |\n| JAGS | — | `scripts/cross-platform/JAGS/setup_jags.sh` | `jags scriptfile` |\n| JASP | — | `scripts/cross-platform/JASP/setup_jasp.sh` | Check install |\n| Julia | — | `scripts/cross-platform/Julia/setup_julia.sh` | `julia -v` |\n| KNIME | — | `scripts/cross-platform/KNIME/setup_knime.sh` | Check install |\n| Mathematica | — | `scripts/cross-platform/Mathematica/setup_mathematica.sh` | `wolframscript -code \"Print[1]\"` |\n| Matlab | — | `scripts/cross-platform/Matlab/setup_matlab.sh` | `matlab -batch \"exit\"` |\n| Minitab | — | `scripts/cross-platform/Minitab/setup_minitab.sh` | No CLI (manual GUI launch; `mtb.exe /run` opens GUI) |\n| Mplus | — | `scripts/cross-platform/Mplus/setup_mplus.sh` | `mplus model.inp` |\n| OpenBUGS | — | `scripts/cross-platform/OpenBUGS/setup_openbugs.sh` | `openbugs --help` |\n| Orange | — | `scripts/cross-platform/Orange/setup_orange.sh` | `orange-canvas --help` |\n| OxMetrics | — | `scripts/cross-platform/OxMetrics/setup_oxmetrics.sh` | `oxmetrics --help` |\n| PSPP | — | `scripts/cross-platform/PSPP/setup_pspp.sh` | Check install |\n| Rattle | — | `scripts/cross-platform/Rattle/setup_rattle.sh` | `rattle --cli` |\n| SHAZAM | — | `scripts/cross-platform/SHAZAM/setup_shazam.sh` | `shazam commands.txt` |\n| Stat/Transfer | `scripts/cross-platform/StatTransfer/setup_stattransfer.sh` | `scripts/windows-only/StatTransfer/statsoft-stattransfer.ps1` + `st` (built-in) | `st -v` |\n| TSP | — | `scripts/cross-platform/TSP/setup_tsp.sh` | `tsp commands.txt` |\n| Tanagra | — | `scripts/cross-platform/Tanagra/setup_tanagra.sh` | `tanagra --help` |\n| Weka | — | `scripts/cross-platform/Weka/setup_weka.sh` | Check install |\n| jamovi | — | `scripts/cross-platform/jamovi/setup_jamovi.sh` | Check install |\n\n---\n\n## AMOS\n\n### Introduction\n\nAMOS is a Structural Equation Modeling (SEM) software from the SPSS family, Windows-only. After installation, it can be found in the Start Menu, and displays a GUI when running.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ❌ (no CLI) | ⚠️⚠️⚠️ GUI only |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Configuration Completion Notes\n\n- ⚠️⚠️⚠️ No CLI mode — GUI launches when called (unavoidable)\n- 💡 Suitable for SEM, path analysis, confirmatory factor analysis\n\n---\n\n## CmdStan\n\n### Introduction\n\nCmdStan is the command-line interface for the Stan statistical platform, pure CLI support, completely splash-free, for Bayesian MCMC sampling.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- ✅ Suitable for Bayesian statistical modeling and MCMC sampling\n- 💡 Can also use R `rstan` or Python `cmdstanpy` to call Stan\n\n---\n\n## EViews\n\n### Introduction\n\nEViews is an econometrics time series analysis software (Windows-only), has CLI support (batch mode), may have splash screen.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (batch mode) | ⚠️ May have splash screen |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Batch Command\n\n```powershell\n# Run EViews program file\n\"EViews.exe\" \"program.prg\" /r\n```\n\n### Configuration Completion Notes\n\n- ⚠️ EViews batch mode may have splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for time series analysis, regression, forecasting\n\n---\n\n## GenStat\n\n### Introduction\n\nGenStat is an agricultural statistics and data analysis software, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Suitable for agricultural statistics, experimental design, data analysis\n\n---\n\n## GraphPad Prism\n\n### Introduction\n\nGraphPad Prism is scientific graphing and statistical analysis software, **does not have a CLI mode** — calling it will launch the GUI (unavoidable).\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ❌ (no CLI) | ⚠️⚠️⚠️ GUI only |\n| macOS | ✅ | ❌ (no CLI) | ⚠️⚠️⚠️ GUI only |\n| Linux | ❌ | ❌ | — |\n\n### Installation Paths\n\n**Windows**:\n- `C:\\Program Files\\GraphPad\\Prism 8\\prism.exe`\n- `C:\\Program Files\\GraphPad\\Prism 9\\prism.exe`\n- `C:\\Program Files\\GraphPad\\Prism 10\\prism.exe`\n\n**macOS**:\n- `/Applications/GraphPad Prism.app/Contents/MacOS/GraphPad Prism`\n\n### How to Launch (manual GUI launch only, no CLI batch)\n\n> ⚠️ GraphPad Prism **has no CLI mode** and cannot be run silently/batch via command line.\n> This skill does **not** provide any `prism.exe` command-line call, and does **not create or modify** any GraphPad Prism project/data files (including `.pzfx`); only the following are supported:\n> 1. Manually double-click to open the GUI (or the user launches it themselves);\n> 2. The user operates their project/data files within GraphPad Prism themselves.\n\n### ⚠️ Important Limitation\n\nGraphPad Prism **has no CLI mode**, calling it will launch the GUI. This differs from SPSS (Production Facility), R (Rscript), Stata (batch mode).\n\n### Alternatives\n\n- ⚠️ This skill does NOT support any automation that creates or modifies `.pzfx` files in the background (including Python `prismWriter`); such operations are out of scope and must be performed manually by the user in their own GraphPad Prism environment.\n\n### Configuration Completion Notes\n\n- ⚠️⚠️⚠️ No CLI mode — GUI launches when called (unavoidable)\n- 💡 This skill provides detection and manual-launch guidance only; it NEVER creates or modifies Prism `.pzfx` project/data files\n\n---\n\n## Gretl\n\n### Introduction\n\nGretl is a free, cross-platform econometrics software with pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Batch Command\n\n```bash\n# Run script\ngretlcli -b script.inp\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- ✅ Free software, suitable for econometrics analysis\n\n---\n\n## H2O.ai\n\n### Introduction\n\nH2O.ai is an automated machine learning platform, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Suitable for AutoML, deep learning, predictive analytics\n\n---\n\n## JAGS\n\n### Introduction\n\nJAGS (Just Another Gibbs Sampler) is a Bayesian MCMC sampling software, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Batch Command\n\n```bash\njags scriptfile\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Suitable for Bayesian modeling, syntax compatible with WinBUGS/OpenBUGS\n\n---\n\n## JASP\n\n### Introduction\n\nJASP is an open-source statistical analysis software offering both classical and Bayesian statistical methods. Requires GUI to run.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n| macOS | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n| Linux | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n\n### Configuration Completion Notes\n\n- ⚠️⚠️⚠️ JASP requires GUI, cannot fully avoid splash screen\n- 💡 Suitable for academic research and teaching, user-friendly interface\n\n---\n\n## JMP\n\n### Introduction\n\nJMP is an interactive visualization statistical software by SAS, supports JSL script batch processing (`/R` parameter), may have brief splash screen (1-2 seconds) when running.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (`/R` parameter) | ⚠️ Brief (1-2 sec) |\n| macOS | ✅ | ✅ (`/R` parameter) | ⚠️ Brief (1-2 sec) |\n| Linux | ❌ | ❌ | — |\n\n### Installation Paths\n\n**Windows**:\n- `C:\\Program Files\\SAS\\JMP\\JMP.exe`\n- `C:\\Program Files\\JMP\\JMP\\JMP.exe`\n\n**macOS**:\n- `/Applications/JMP.app/Contents/MacOS/JMP`\n\n### Batch Command\n\n```powershell\n# Windows\n\"JMP.exe\" /R \"script.jsl\"\n\n# macOS\nJMP -R \"script.jsl\"\n```\n\n### JSL Script Template\n\n```jsl\n// script.jsl — JMP script\nClear Log();\n\n// Read data\ndt = Open(\"data.csv\");\n\n// Analysis\n[AnalysisPlatform](\n Y(:column1),\n X(:column2)\n);\n\n// Save results\nSave(dt, \"results.jmp\");\nClose(dt, NoSave);\n\n// Exit (batch mode)\nExit();\n```\n\n### ⚠️ Splash Screen Issue\n\nJMP is a GUI application; even when using the `/R` batch mode, it may still display a startup splash screen when running. The splash screen lasts only briefly (1-2 seconds), and JMP will auto-close after the script finishes (if the script ends with `Exit();`).\n\n### Notes\n\n- ⚠️ **The script must end with `Exit();`**, otherwise the JMP GUI stays open\n- **Compared with GraphPad**: GraphPad has no CLI at all, while JMP has a CLI (`/R` parameter) and supports batch processing\n\n### Configuration Completion Notes\n\n- ⚠️ JMP may show a brief splash screen (1-2 sec) when running, unavoidable\n- ⚠️ The script must end with `Exit();`\n\n---\n\n## Julia\n\n### Introduction\n\nJulia is a high-performance scientific computing language, pure CLI support, completely splash-free, suitable for Bayesian statistics and high-performance computing.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Batch Command\n\n```bash\njulia script.jl\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- ✅ High performance, suitable for big data and complex statistical computing\n- 💡 Common packages: Statistics, HypothesisTests, GLM, Turing (Bayesian)\n\n---\n\n## KNIME\n\n### Introduction\n\nKNIME is an open-source data analytics workflow platform, pure CLI support (execute workflows via command line), completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ CLI batch processing supported, completely GUI-free, no splash screen\n- 💡 Suitable for visual workflow orchestration and automated data pipelines\n\n---\n\n## LIMDEP\n\n### Introduction\n\nLIMDEP is an econometrics and discrete choice analysis software (Windows-only), has CLI support, suitable for microeconometrics research.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Batch Command\n\n```powershell\nlimdep commands.txt\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for econometrics analysis\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for discrete choice and limited dependent variable models\n\n---\n\n## Mathematica\n\n### Introduction\n\nMathematica is a mathematical computing and statistical analysis platform developed by Wolfram Research, pure CLI support (`wolframscript`), completely splash-free. Executes Wolfram Language scripts via command line, supporting symbolic computation, numerical analysis, statistical modeling, and visualization.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (`wolframscript.exe`) | ❌ |\n| macOS | ✅ | ✅ (`wolframscript`) | ❌ |\n| Linux | ✅ | ✅ (`wolframscript`) | ❌ |\n\n### Batch Command\n\n```bash\n# Run Wolfram Language script\nwolframscript -file script.wl\n\n# Execute code directly\nwolframscript -code \"Table[i^2, {i, 10}]\"\n\n# Interactive REPL mode\nwolframscript\n\n# Windows explicit call (replaces MathKernel)\n\"C:\\Program Files\\Wolfram Research\\Mathematica\\14.0\\MathKernel.exe\" -noprompt < script.m\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool (`wolframscript`), completely GUI-free, no splash screen\n- ✅ Cross-platform support (Win/Mac/Linux)\n- 💡 Suitable for symbolic mathematics, numerical analysis, statistical modeling, and visualization\n- ⚠️ WolframScript requires a commercial license with periodic activation\n\n---\n\n## Matlab\n\n### Introduction\n\nMatlab is an engineering computation and statistics software, has CLI support (`-batch` mode), completely splash-free (when using `-batch` parameter).\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (`-batch`) | ❌ (with -batch) |\n| macOS | ✅ | ✅ (`-batch`) | ❌ (with -batch) |\n| Linux | ✅ | ✅ (`-batch`) | ❌ (with -batch) |\n\n### Batch Command\n\n```bash\n# Run script (no GUI)\nmatlab -batch \"run('script.m')\"\n```\n\n### Configuration Completion Notes\n\n- ✅ Completely GUI-free when using `-batch` parameter\n- ⚠️ Requires Statistics and Machine Learning Toolbox\n- 💡 Suitable for engineering statistics, signal processing, ML\n\n---\n\n## Microfit\n\n### Introduction\n\nMicrofit is an econometrics time series analysis software (Windows-only), has CLI support.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Batch Command\n\n```powershell\nmicrofit commands.txt\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for econometric time series\n- ⚠️ Windows-only, no macOS/Linux support\n\n---\n\n## Minitab\n\n### Introduction\n\nMinitab is an industrial statistics and Six Sigma software. **`mtb.exe /run` does NOT run headless** — it launches the full Minitab GUI window (observed window title `Minitab - [Untitled]`), so it is not safe for agent-driven batch automation. Treat Minitab as a **GUI-only** tool: detect the install (path / version) and give a manual launch guide, exactly like AMOS / GraphPad / JASP / jamovi.\n\n### Platform Support\n\n| Platform | Supported | Headless CLI | Notes |\n|----------|-----------|--------------|-------|\n| Windows | ✅ | ❌ (`mtb.exe /run` opens GUI) | Detect + manual launch only |\n| macOS | ⚠️ Limited | ❌ | Minitab Web App / remote desktop |\n| Linux | ⚠️ Limited | ❌ | Minitab Web App / remote desktop |\n\n### Configuration Completion Notes\n\n- ⚠️ `mtb.exe /?` is NOT a help flag — it launches the Minitab GUI. Do not use it for detection.\n- ⚠️ `mtb.exe /run \"script.mtb\"` opens the Minitab GUI and may hang waiting on the window; never call it from the agent.\n- 💡 Suitable for quality control and Six Sigma projects; run analyses interactively in the Minitab GUI.\n\n---\n\n## Mplus\n\n### Introduction\n\nMplus is a Structural Equation Modeling (SEM) and latent variable analysis software, has CLI support, suitable for complex statistical modeling.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ❌ | ❌ | — |\n\n### Batch Command\n\n```bash\nmplus model.inp\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for SEM and latent variable analysis\n- 💡 Suitable for multilevel, growth, mixture models\n\n---\n\n## NCSS\n\n### Introduction\n\nNCSS is a statistical analysis software (Windows-only), has CLI support (batch mode), suitable for medical statistics, sample size calculation, etc.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (batch mode) | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for statistical analysis\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for medical statistics, sample size calculation, data analysis\n\n---\n\n## NLOGIT\n\n### Introduction\n\nNLOGIT is a discrete choice econometrics software (Windows-only), has CLI support, an extended version of LIMDEP.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Batch Command\n\n```powershell\nnlogit commands.txt\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for discrete choice analysis\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for Logit, Probit, Mixed Logit models\n\n---\n\n## OpenBUGS\n\n### Introduction\n\nOpenBUGS is an open-source Bayesian MCMC sampling software, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Suitable for Bayesian modeling, open-source WinBUGS alternative\n\n---\n\n## Orange\n\n### Introduction\n\nOrange is an open-source visual data mining and ML software, has CLI support (Python-based), may display graphical interface when running.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ⚠️ May have |\n| macOS | ✅ | ✅ | ⚠️ May have |\n| Linux | ✅ | ✅ | ⚠️ May have |\n\n### Configuration Completion Notes\n\n- ⚠️ CLI support available, but some operations may involve GUI\n- 💡 Suitable for visual data mining, ML, data exploration\n\n---\n\n## OriginLab Origin\n\n### Introduction\n\nOrigin is a professional scientific graphing and data analysis software with over 1 million users worldwide, deeply embedded in Chinese research institutions. Supports LabTalk script batch processing, can execute data analysis tasks via command line.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (LabTalk script) | ❌ |\n| macOS | ✅ | ⚠️ Limited | ⚠️ May have |\n| Linux | ❌ | ❌ | — |\n\n### Installation Paths\n\n**Windows**:\n- `C:\\Program Files\\OriginLab\\Origin2025\\Origin95.exe`\n- `C:\\Program Files\\OriginLab\\Origin2024\\Origin95.exe`\n\n### Batch Command\n\n```powershell\n# Windows — run LabTalk script\n\"origin97\" -h \"script.ogs\"\n\n# Or compile and execute via Origin C\n```\n\n### Configuration Completion Notes\n\n- ✅ LabTalk CLI support, completely GUI-free (-h mode)\n- ✅ Over 1M users worldwide, widely used in Chinese research institutions\n- 💡 Suitable for scientific graphing, data analysis, batch figure generation\n\n---\n\n## OxMetrics\n\n### Introduction\n\nOxMetrics is an econometrics software suite, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Suitable for econometrics, financial time series, predictive modeling\n\n---\n\n## PSPP\n\n### Introduction\n\nPSPP is an open-source alternative to SPSS, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Open-source, SPSS syntax compatible\n\n---\n\n## Q (MRKS)\n\n### Introduction\n\nQ (MRKS) is a market research analysis software (Windows-only), supports CLI mode for market research analytics.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, suitable for market research analysis\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for survey analysis, statistical testing, report generation\n\n---\n\n## Rattle\n\n### Introduction\n\nRattle is a visual data mining interface for R, has CLI support (`--cli` mode), suitable for data mining tasks.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ CLI support available (`--cli` mode), completely GUI-free\n- 💡 Suitable for data exploration, statistical analysis, ML modeling\n\n---\n\n## SHAZAM\n\n### Introduction\n\nSHAZAM is an econometrics software, has CLI support, suitable for economic statistics and econometric analysis.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Batch Command\n\n```bash\nshazam commands.txt\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, completely GUI-free, no splash screen\n- 💡 Suitable for econometrics, statistical analysis, data processing\n\n---\n\n## SPSS Modeler\n\n### Introduction\n\nSPSS Modeler is IBM's data mining and predictive analytics software (Windows-only), executes .str stream files via the `clemb.exe` command-line tool.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (`clemb.exe`) | ❌ |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Installation Paths\n\n**Windows**:\n- `C:\\Program Files\\IBM\\SPSS\\Modeler\\18.0\\clemb.exe`\n\n### Batch Command\n\n```powershell\n# Execute stream file in local mode\nclemb -local -stream \"model.str\" -execute\n\n# Python script mode\nclemb -local -pyscript \"script.py\" -execute\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI execution via `clemb.exe`, completely GUI-free, no splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for data mining, predictive modeling, ML pipelines\n\n---\n\n## Stat/Transfer\n\n### Introduction\n\nStat/Transfer is a pure CLI data format conversion tool, completely GUI-free, suitable for automation. Supports format conversion between Stata, SPSS, SAS, R, Excel, etc.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Command Line Format\n\n```bash\n# Single-file conversion\n\"[ST_EXE_PATH]\" in.sas7bdat out.dta\n\n# Batch conversion\n\"[ST_EXE_PATH]\" in\\*.sav out\\*.dta\n\n# Command-file batch\n\"[ST_EXE_PATH]\" myfile.stcmd\n```\n\n### Supported Formats\n\n| Format | Extension |\n|--------|-----------|\n| Stata | `.dta` |\n| SPSS | `.sav`, `.por` |\n| SAS | `.sas7bdat`, `.xpt` |\n| R | `.rda`, `.rds` |\n| Excel | `.xlsx`, `.xls` |\n| CSV | `.csv`, `.tsv` |\n\n### Role in AI Workflow\n\n```\nHistorical data (.sas7bdat)\n ↓ Stat/Transfer CLI\nIntermediate format (.dta / .sav / .csv)\n ↓ R / Stata / SPSS CLI\nAnalysis results\n ↓ Stat/Transfer CLI\nDelivery format (.xlsx / .sas7bdat)\n```\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, suitable for automation\n- 💡 Role in AI workflow: data format conversion bridge\n\n---\n\n## Statistica\n\n### Introduction\n\nStatistica is a data mining and machine learning software (Windows-only), has CLI support (SVB script batch processing), may have splash screen.\n\n> ⚠️ **Detection-only + manual guidance (SDI-1 safety boundary)**: `setup_statistica.ps1` is detection-only and never writes `config.json`. Executing an SVB script goes through the guarded runner `statsoft-statistica.ps1` with a `Test-UserAuthorizedToRun` gate (same as SPSS/R runners).\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ (SVB script) | ⚠️ May have splash screen |\n| macOS | ❌ | ❌ | — |\n| Linux | ❌ | ❌ | — |\n\n### Detection & Manual-Guidance Notes\n\n- ⚠️ `setup_statistica.ps1` detection-only, writes no config.json\n- ⚠️ Executing an SVB requires the guarded runner + explicit confirmation\n- ⚠️ Statistica batch mode may have splash screen\n- ⚠️ Windows-only, no macOS/Linux support\n- 💡 Suitable for data mining, ML, statistical analysis\n\n---\n\n## Tanagra\n\n### Introduction\n\nTanagra is an open-source data mining and ML software, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Open-source, suitable for data mining and ML teaching/research\n\n---\n\n## TSP\n\n### Introduction\n\nTSP is a time series and econometrics software, has CLI support, suitable for time series analysis and econometric modeling.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Batch Command\n\n```bash\ntsp commands.txt\n```\n\n### Configuration Completion Notes\n\n- ✅ CLI support available, completely GUI-free, no splash screen\n- 💡 Suitable for time series analysis, econometrics, financial modeling\n\n---\n\n## Weka\n\n### Introduction\n\nWeka is an open-source machine learning and data mining software, pure CLI support, completely splash-free.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ✅ | ❌ |\n| macOS | ✅ | ✅ | ❌ |\n| Linux | ✅ | ✅ | ❌ |\n\n### Configuration Completion Notes\n\n- ✅ Pure CLI tool, completely GUI-free, no splash screen\n- 💡 Open-source, suitable for ML, data mining, predictive analytics\n\n---\n\n## jamovi\n\n### Introduction\n\njamovi is an open-source statistical analysis software with a spreadsheet-style data analysis interface. Requires GUI to run.\n\n### Platform Support\n\n| Platform | Supported | CLI Support | Splash Screen |\n|----------|-----------|-------------|---------------|\n| Windows | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n| macOS | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n| Linux | ✅ | ❌ (no pure CLI) | ⚠️⚠️⚠️ Requires GUI |\n\n### Configuration Completion Notes\n\n- ⚠️⚠️⚠️ jamovi requires GUI, cannot fully avoid splash screen\n- 💡 Open-source, user-friendly, suitable for academic research and teaching\n\n---\n\nArchive v2.7.1: 83 files, 228256 bytes\n\nFiles: ADDITIONAL_SOFTWARE.md (32487b), AGENTS.md (3217b), assets/icon.svg (1601b), CHANGELOG.md (41121b), LICENSE (1105b), README_zh-CN.md (10713b), README.md (10524b), references/command-examples.md (14941b), references/completion-prompts.md (22007b), references/config-templates.md (8918b), references/platform-support.md (1199b), references/trust-and-safety.md (1015b), references/version-specifics.md (14286b), references/workflow.md (1292b), scripts/common/write_config.py (6897b), scripts/cross-platform/_platform-detect.sh (2032b), scripts/cross-platform/CmdStan/setup_cmdstan.sh (4092b), scripts/cross-platform/CmdStan/statsoft-cmdstan.py (11057b), scripts/cross-platform/GenStat/setup_genstat.sh (3675b), scripts/cross-platform/Gretl/setup_gretl.sh (8243b), scripts/cross-platform/H2O/setup_h2o.sh (4169b), scripts/cross-platform/JAGS/setup_jags.sh (3928b), scripts/cross-platform/jamovi/setup_jamovi.sh (3287b), scripts/cross-platform/JASP/setup_jasp.sh (3130b), scripts/cross-platform/Julia/setup_julia.sh (9694b), scripts/cross-platform/KNIME/setup_knime.sh (3070b), scripts/cross-platform/Mathematica/setup_mathematica.sh (7046b), scripts/cross-platform/Matlab/setup_matlab.sh (10324b), scripts/cross-platform/Minitab/setup_minitab.sh (6832b), scripts/cross-platform/Mplus/setup_mplus.sh (2995b), scripts/cross-platform/OpenBUGS/setup_openbugs.sh (3953b), scripts/cross-platform/Orange/setup_orange.sh (4700b), scripts/cross-platform/OxMetrics/setup_oxmetrics.sh (3857b), scripts/cross-platform/PSPP/setup_pspp.sh (3020b), scripts/cross-platform/R/setup_r.sh (17033b), scripts/cross-platform/Rattle/setup_rattle.sh (5604b), scripts/cross-platform/SAS/setup_sas.sh (12696b), scripts/cross-platform/scan/scan_all.sh (8883b), scripts/cross-platform/SHAZAM/setup_shazam.sh (3858b), scripts/cross-platform/Stata/setup_stata.sh (10877b), scripts/cross-platform/StatTransfer/setup_stattransfer.sh (11625b), scripts/cross-platform/Tanagra/setup_tanagra.sh (3653b), scripts/cross-platform/TSP/setup_tsp.sh (3611b), scripts/cross-platform/Weka/setup_weka.sh (3384b), scripts/windows-only/AMOS/setup_amos.ps1 (8963b), scripts/windows-only/AMOS/setup_amos.py (6842b), scripts/windows-only/EViews/setup_eviews.ps1 (4621b), scripts/windows-only/EViews/statsoft-eviews.ps1 (3405b), scripts/windows-only/GraphPad/setup_graphpad.ps1 (8357b), scripts/windows-only/GraphPad/statsoft-graphpad.ps1 (4224b), scripts/windows-only/JMP/setup_jmp.ps1 (7989b), scripts/windows-only/JMP/statsoft-jmp.ps1 (7016b), scripts/windows-only/Limdep/setup_limdep.ps1 (4699b), scripts/windows-only/Mathematica/setup_mathematica.ps1 (6021b), scripts/windows-only/Microfit/setup_microfit.ps1 (4456b), scripts/windows-only/Minitab/setup_minitab.ps1 (6289b), scripts/windows-only/Mplus/setup_mplus.ps1 (4315b), scripts/windows-only/NCSS/setup_ncss.ps1 (4934b), scripts/windows-only/NLOGIT/setup_nlogit.ps1 (4101b), scripts/windows-only/Origin/setup_origin.ps1 (4897b), scripts/windows-only/Q_MRKS/setup_q.ps1 (4851b), scripts/windows-only/scan/scan_all.ps1 (21822b), scripts/windows-only/SHAZAM/setup_shazam.ps1 (4498b), scripts/windows-only/SPSS/_data_info.py (980b), scripts/windows-only/SPSS/_spss_runner.py (1325b), scripts/windows-only/SPSS/run-spss-internal.py (6942b), scripts/windows-only/SPSS/setup_modeler.ps1 (5027b), scripts/windows-only/SPSS/setup_spss.ps1 (17961b), scripts/windows-only/SPSS/spss_helper.py (25798b), scripts/windows-only/SPSS/statsoft-modeler.ps1 (6848b), scripts/windows-only/SPSS/statsoft-spss.ps1 (19788b), scripts/windows-only/Statistica/setup_statistica.ps1 (6885b), scripts/windows-only/Statistica/statsoft-statistica.ps1 (3668b), scripts/windows-only/statsoft-r.ps1 (7537b), scripts/windows-only/statsoft-sas.ps1 (7298b), scripts/windows-only/StatTransfer/statsoft-stattransfer.ps1 (13209b), skill-card.md (3189b), SKILL.md (7180b), tests/example_workflow.md (7923b), tests/README.md (3176b)\n\nFile v2.7.1:SKILL.md\n\n---\nname: statsoft-cli\nslug: statsoft-cli\ndisplayName: 统计软件接入助手 / Statsoft-CLI\ncn_name: 统计软件接入助手\nversion: \"2.7.1\"\nsummary: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。\"\nlicense: MIT\ndescription: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation.\"\ntriggers:\n - \"SPSS\"\n - \"SPSS Statistics\"\n - \"R\"\n - \"R命令行\"\n - \"Stata\"\n - \"SAS\"\n - \"统计软件\"\n - \"连接统计软件\"\n - \"statsoft-cli\"\n - \"connect statistical software\"\nmetadata:\n {\n \"openclaw\": { \"emoji\": \"🛠️\", \"icon\": \"assets/icon.svg\" },\n \"authors\": [\"medstatstar\", \"phoe-zip\"],\n \"contributors\": [\"medstatstar\", \"phoe-zip\"],\n \"version\": \"2.7.1\",\n \"license\": \"MIT\",\n \"tags\": [\"Statistical Software\", \"CLI\", \"R\", \"SPSS\", \"Stata\", \"SAS\", \"Bayesian\", \"Machine Learning\", \"Econometrics\", \"SEM\", \"Data Mining\"],\n \"homepage\": \"https://github.com/medstatstar/statsoft-cli\",\n \"repository\": \"https://github.com/medstatstar/statsoft-cli\"\n }\n---\n\n## Language\n\nPick the README that matches your language for human-readable, language-specific guides:\n\n- **English guide** → [README.md](https://github.com/medstatstar/statsoft-cli/blob/main/README.md)\n- **中文指南** → [README_zh-CN.md](https://github.com/medstatstar/statsoft-cli/blob/main/README_zh-CN.md)\n\nThis skill responds in the user's current input language (Chinese or English) and auto-detects / switches accordingly. The runtime scripts embed a locale check (`$script:isZH` in PowerShell, `SCRIPT_LANG` in Bash) so all user-facing prompts switch to Chinese on a `zh-*` UI culture and to English otherwise. Code comments and documentation are English-only.\n\nThe SKILL.md body, `references/*.md`, and `ADDITIONAL_SOFTWARE.md` are English-only and agent-facing; runtime command prompts switch to Chinese / English by locale. For end-to-end walkthroughs, examples, and troubleshooting in your language, open the README above.\n\n## Overview\n\nActivates historical code assets locked in statistical software (syntax, scripts, projects) and wires them into AI workflows via automated detection, configuration, and execution.\n\n## Core Functions\n\nCovers 34+ statistical / data-science packages, auto-routed by platform; non-Windows auto-hides incompatible software:\n\n- **Cross-platform (Win / Mac / Linux, CLI)**: R, Stata, SAS, CmdStan, GenStat, Gretl, H2O.ai, JAGS, Julia, KNIME, Mathematica, Matlab, OpenBUGS, Orange, OxMetrics, PSPP, Rattle, SHAZAM, Stat/Transfer, Tanagra, TSP, Weka\n- **Windows + limited cross-platform**: Mplus\n- **Windows-only CLI**: SPSS Statistics, EViews, JMP, LIMDEP, Microfit, NCSS, NLOGIT, Origin, Q(MRKS), SPSS Modeler, Statistica\n- **GUI-only detection + manual launch guide**: AMOS, GraphPad Prism, JASP, jamovi, Minitab (never drive batch via CLI; `mtb.exe /run` opens the Minitab GUI, not headless)\n\nFull platform matrix in `references/platform-support.md`; extended config in `ADDITIONAL_SOFTWARE.md`.\n\n## Execution Workflow\n\n1. **Detect Platform** — cross-platform `source scripts/cross-platform/_platform-detect.sh` (sets `$PLATFORM`/`$OS`/`$ARCH`); Windows handled inside `.ps1` scripts, no source\n2. **Pre-scan Confirmation** — before any scan, MUST prompt and wait:\n - Prompt (English by default; auto-switched to Chinese on a `zh-*` locale): \"⚠️ Auto-scan may take a while (~30s on Windows). If you have ≤3 packages, specify paths to skip. Your choice?\" Options: A) Auto-scan B) Specify paths\n - A → step 3; B → skip scan, go to step 4\n3. **System Scan** (only if A) — batch-detect installed software:\n - Windows: `scripts/windows-only/scan/scan_all.ps1`; Mac/Linux: `scripts/cross-platform/scan/scan_all.sh`\n - Output JSON: `{\"R\":{\"installed\":true,\"path\":\"...\",\"version\":\"...\"},...}`\n - By default only the `installed` boolean is returned; path / version disclosed only with `STATSOFT_AUTO_WRITE=1` or `STATSOFT_CONFIRM=1`+interactive y (note: `STATSOFT_REVEAL` controls per-software setup-time output only, not batch scan results)\n4. **Select Config Mode** — batch / specified / single-software (calls individual `setup_*.ps1` or `setup_*.sh`)\n5. **Detect & Setup** — route to the platform script; non-Windows auto-hides incompatible software\n6. **Save Config** — detect-only by default; writes `config.json` only with explicit authorization (`STATSOFT_AUTO_WRITE=1` or `STATSOFT_CONFIRM=1` + interactive y)\n7. **Output Summary** — per `references/completion-prompts.md` template\n\n## Default-Deny Gates\n\nAll persistence and sensitive operations are **off by default** and require explicit authorization (fail-closed), consistent with the scripts:\n\n| Gate | Effect | Default |\n|------|--------|---------|\n| `STATSOFT_AUTO_WRITE=1` | Persist `config.json` (non-interactive / agent context) | off |\n| `STATSOFT_CONFIRM=1` + TTY y | Persist after interactive confirmation | off |\n| `STATSOFT_REVEAL=1` | Reveal path / version details during detection | off |\n| `STATSOFT_VERIFY=1` | Allow launching third-party binaries for version / verification | off |\n| `STATSOFT_CMDSTAN_RUN=1` | Allow compiling & running user Stan models (untrusted native code) | off |\n\nAll writes go through `scripts/common/write_config.py`: accepts only the canonical `config.json` under the skill root, and before writing takes a timestamped backup (`config.json.bak.yyyymmdd_hhmmss`) then atomic-replaces.\n\n## Core Permissions\n\n- **Local file read-write** — `config.json`, temp scripts\n- **Process execution** — statistical software binaries\n- **Network access** — CRAN / Anaconda repos\n\n## Trust & Safety\n\nThis skill performs high-risk operations; understand the risk levels before use:\n\n| Risk | Level |\n|------|-------|\n| Execute local executables | 🔴 High |\n| Download & install software | 🔴 High |\n| Execute user scripts (e.g. `.sps` via SPSS Python) | 🔴 High |\n| Modify config.json | 🟡 Medium |\n| Network access | 🟡 Medium |\n\n**Pre-flight**: ✅ review all scripts; ✅ confirm config.json changes (auto-backup); ✅ confirm any downloads; ✅ inspect generated commands for sensitive projects.\n\n## Reference Files\n\n- `ADDITIONAL_SOFTWARE.md` — extended software config (31 packages)\n- `references/command-examples.md` — per-software CLI command examples\n- `references/config-templates.md` — `config.json` templates & field reference\n- `references/version-specifics.md` — version differences\n- `references/completion-prompts.md` — completion prompt templates\n- `references/trust-and-safety.md` — risk levels & pre-flight details\n- `references/workflow.md` — workflow gating details\n- `references/platform-support.md` — full platform support matrix\n- `tests/` — automated test scripts\n\nFile v2.7.1:README.md\n\n# statsoft-cli\n\n[🇨🇳 中文 (Chinese)](./README_zh-CN.md) | [🇬🇧 English](./README.md)\n\n> 📝 **Changelog**: [CHANGELOG.md](./CHANGELOG.md)\n\n---\n\nCross-platform statistical software CLI integration for AI Agent (such as WorkBuddy / OpenClaw). \n\nSupports 34 statistical software packages: SPSS Statistics, R, Stata, SAS, AMOS, CmdStan, EViews, GenStat, GraphPad Prism, Gretl, H2O.ai, JAGS, JASP, JMP, Julia, KNIME, LIMDEP, Mathematica, Matlab, Microfit, Minitab, Mplus, NCSS, NLOGIT, OpenBUGS, Orange, OriginLab Origin, OxMetrics, PSPP, Q (MRKS), Rattle, SHAZAM, Stat/Transfer, Statistica, TSP, Tanagra, Weka, jamovi. (Note: AMOS, GraphPad Prism, JASP, and jamovi are GUI-only — they can be detected and launched but have no CLI batch mode.)\n\nMultiple versions of the same software can coexist — for example, R4.5 and R4.0 can coexist, with a default version configured. Switch versions seamlessly by mentioning it in your prompt.\n\nNote: If your goal is to **seamlessly read various statistical data files or convert between formats without loss**, we strongly recommend installing the standalone skill **statdata-transfer**. This skill can perfectly achieve data format conversion without relying on any statistical software support.\n\n## Purpose\n\nMany statistical software packages have CLI (Command Line Interface) execution modes, but not everyone knows how to use them. This skill integrates these tools into the AI Agent environment for unified access, enabling statisticians to fully leverage these tools' capabilities. **The core value of this skill lies in activating historical code assets and solving the reusability problem in AI workflow automation**. Over years of project accumulation, teams have gathered reusable analysis code—R modeling scripts, SPSS syntax files, SAS macro programs, Stata do-files—and this skill brings them into a unified execution framework as standard AI workflow nodes.\n\n## Quick Start\n\n### One-Click Setup\n\nTrigger in AI Agent conversation:\n```\nConnect SPSS 26\nConfigure R statistical software\n```\n\nThe Agent will auto-detect the software path. **By default it only reports the detected path and does NOT modify `config.json`** (fail-closed / detection-only). To persist the result, opt in explicitly: set `STATSOFT_AUTO_WRITE=1` (non-interactive / agent) or `STATSOFT_CONFIRM=1` and answer `y` at the prompt (interactive).\n\n### Verify Installation\n\n```\nRun SPSS syntax: SHOW VERSION.\nConvert data.sav to data.dta\n```\n\n---\n\n## Use Cases\n\n### 1. Multi-Software Mixed Workflow\nSeamlessly invoke R modeling + SPSS descriptive + Stata data prep in a single AI Agent session.\n\n### 2. Historical Code Asset Reuse\nBring R scripts, SPSS syntax, SAS macros, Stata do-files into the AI workflow as standard nodes.\n\n### 3. Data Format Conversion\nStat/Transfer (a supported CLI tool) migrates data between software (SAS ↔ SPSS ↔ Stata ↔ Excel). For general format conversion without statistical software, use the statdata-transfer skill.\n\n### 4. SPSS Statistics Splash-Free Batch\nExecute `.sps` syntax via built-in Python engine, skipping splash screen.\n\n### 5. SAS Batch Automation\nSchedule SAS macro programs via SAS CLI for periodic reporting.\n\n### 6. SPSS Modeler Batch\nExecute `.str` streams via `clemb.exe` in local mode.\n\n> 📚 **Full details for all 34 software packages** → see [`ADDITIONAL_SOFTWARE.md`](./ADDITIONAL_SOFTWARE.md)\n\n---\n\n## Important Notes\n\nSplash Screen: The 34 supported statistical software packages have **varying levels of CLI support**. Some are fully command-line driven, while others may still require GUI interaction during use. The specific behavior varies by software:\n\n- ✅ **Pure CLI, no splash screen** (e.g., R, Stata, SAS, CmdStan, Julia, Gretl, Mathematica)\n- ⚠️ **CLI mode with brief splash screen** (e.g., JMP, Minitab, EViews, Statistica)\n- 🔴 **GUI required, cannot be avoided** (e.g., AMOS, GraphPad Prism, jamovi, JASP)\n\nAfter configuration is complete, the AI Agent will provide detailed notifications about the behavior of each software.\n\n---\n\n## Excluded Software\n\nThe following software was evaluated but not included due to listed reasons. For data format conversion without statistical software dependency, see the statdata-transfer skill.\n\n| Software | Reason |\n|----------|--------|\n| Systat | Market severely squeezed by SPSS/R/Python, user base shrinking |\n| MaxStat | Niche positioning, very few users, limited functionality |\n| SmartPLS | GUI-only, no CLI or batch mode |\n| WinBUGS | Fully superseded by OpenBUGS (both Bayesian MCMC sampling) |\n\n---\n\n## Platform Support\n\n### Core Software\n\n| Software | Windows Script | Cross-Platform Script | Verify |\n|----------|---------------|----------------------|--------|\n| SPSS Statistics | `scripts/windows-only/SPSS/setup_spss.ps1` | — | `stats.com -production silent -nologo \"exit.spj\"` |\n| R | `scripts/windows-only/statsoft-r.ps1` | `scripts/cross-platform/R/setup_r.sh` | `Rscript --version` |\n| Stata | — | `scripts/cross-platform/Stata/setup_stata.sh` | `stata-mp -b do \"exit\"` |\n| SAS | `scripts/windows-only/statsoft-sas.ps1` | `scripts/cross-platform/SAS/setup_sas.sh` | `sas -version` |\n\n(Full routing table with all additional software packages — see ADDITIONAL_SOFTWARE.md)\n\n## Project Structure\n\n```\nstatsoft-cli/\n├── SKILL.md # Main skill file\n├── README_zh-CN.md # Chinese README\n├── ADDITIONAL_SOFTWARE.md # Extended software configs\n├── LICENSE # MIT license\n├── config.json.example # Config template\n├── scripts/\n│ ├── cross-platform/ # Cross-platform setup scripts\n│ │ ├── _platform-detect.sh # Platform detection\n│ │ ├── scan/ # System scan scripts\n│ │ │ └── scan_all.sh # Batch detection (Linux/Mac/Win)\n│ │ ├── R/ # R setup\n│ │ ├── Stata/ # Stata setup\n│ │ ├── SAS/ # SAS setup\n│ │ ├── CmdStan/ # CmdStan (Bayesian MCMC)\n│ │ ├── Weka/ # Weka (Data Mining)\n│ │ ├── KNIME/ # KNIME (Workflow)\n│ │ ├── jamovi/ # jamovi (Stats)\n│ │ ├── JASP/ # JASP (Stats)\n│ │ ├── PSPP/ # PSPP (SPSS alternative)\n│ │ ├── Mplus/ # Mplus (SEM, Win/Mac)\n│ │ ├── JAGS/ # JAGS (Bayesian MCMC)\n│ │ ├── SHAZAM/ # SHAZAM (Econometrics)\n│ │ ├── OxMetrics/ # OxMetrics (Econometrics)\n│ │ ├── TSP/ # TSP (Time Series)\n│ │ ├── Tanagra/ # Tanagra (Data Mining)\n│ │ ├── Orange/ # Orange (Data Mining)\n│ │ ├── H2O/ # H2O.ai (AutoML)\n│ │ ├── GenStat/ # GenStat (Statistics)\n│ │ ├── Mathematica/ # Mathematica (Math/Stats)\n│ │ ├── Rattle/ # Rattle (R Data Mining)\n│ │ └── OpenBUGS/ # OpenBUGS (Bayesian)\n│ └── windows-only/ # Windows-only scripts\n│ ├── scan/\n│ │ └── scan_all.ps1 # Batch detection (Windows, registry-based)\n│ ├── SPSS/ # SPSS Statistics + Modeler\n│ ├── JMP/ # JMP JSL batch\n│ ├── GraphPad/ # GraphPad Prism\n│ ├── EViews/ # EViews econometrics\n│ ├── Statistica/ # Statistica data mining\n│ ├── StatTransfer/ # Stat/Transfer data conversion\n│ ├── Mplus/ # Mplus (Win/Mac)\n│ ├── AMOS/ # AMOS (SPSS family)\n│ ├── Q_MRKS/ # Q Research (MRKS)\n│ ├── Limdep/ # LIMDEP (Econometrics)\n│ ├── NLOGIT/ # NLOGIT (Discrete Choice)\n│ ├── SHAZAM/ # SHAZAM (Econometrics)\n│ ├── Microfit/ # Microfit (Time Series)\n│ ├── statsoft-r.ps1 # R Windows wrapper\n│ └── statsoft-sas.ps1 # SAS Windows wrapper\n├── references/ # Reference files\n│ ├── command-examples.md # CLI examples\n│ ├── version-specifics.md # Version differences\n│ ├── completion-prompts.md # Completion templates\n│ └── config-templates.md # Config templates\n└── tests/ # Test files\n\n## Usage\n\nThis skill activates only on an **explicit, narrowly scoped request** that names the target tool and action (for example `configure R`, `run Stata `, `convert data.sav to data.dta`). Free-form phrases like \"configure statistical software\" are intentionally not auto-activated for high-risk execution.\n\nTrigger examples (require naming the tool/action):\n\n```\nConnect SPSS 26\nConfigure R statistical software\nConvert data.sav to data.dta\nRun a Stata .do file in batch mode\n```\n\nBefore any execution, install, network fetch, or persistent write, the skill requires explicit confirmation (interactive) or an opt-in environment flag (`STATSOFT_AUTO_WRITE=1` / `STATSOFT_CONFIRM=1`). Read-only detection is the default.\n\nAuthorization & persistence model (explicit, to avoid ambiguity): the opt-in flags above are set **by the user** — the skill only **reads** them and **never writes** them or any other environment variable. The **only** file the skill may persist is its own `config.json`, and **only after** the explicit opt-in described above (with a timestamped `config.json.bak.*` backup; delete `config.json` to roll back). The skill does **not** write `~/.workbuddy/MEMORY.md` or anything outside its own directory.\n\nNon-trigger examples (treated as ordinary conversation, NOT activated):\n\n```\nI read a paper about R\nCan you explain what Stata is?\n```\n\n## Trust & Safety\n\nThis skill executes **high-risk operations** (running local executables, modifying configs, network access). See SKILL.md for full Trust & Safety documentation.\n\n## License\n\n[MIT](LICENSE)\n\nFile v2.7.1:tests/README.md\n\n# SPSS Splash-free Call Test / SPSS 无闪屏调用测试\n\n## Test Purpose\n\n验证 SPSS 无闪屏调用方式是否正常工作。\n\nVerify that the SPSS splash-free call method works correctly.\n\n> ⚠️ **副作用提示 / Side effects**：运行本测试会**执行第三方 SPSS 二进制**，并在磁盘上**写入文件** `test-data.sav`（约 5 条记录）。这是测试的预期产物，仅供手动执行；请勿在自动化流程中静默运行。测试完成后请参见文末「清理 / Cleanup」删除该文件。\n>\n> Running this test **executes the third-party SPSS binary** and **writes a file** `test-data.sav` (~5 rows) to disk. This is an expected artifact of a manually-run test — do not run it silently in automation. See \"Cleanup\" at the end to remove it afterward.\n\n## Test Method\n\n### Preferred Method (Completely Splash-free)\n\n使用 SPSS 内置 Python 的 `spss` 模块直接运行语法，不调用 `stats.exe`，完全无 GUI。\n\nUse SPSS built-in Python's `spss` module to run syntax directly, without calling `stats.exe`, completely GUI-free.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[SPSS_PYTHON_PATH]\" \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" run-internal \"[SPS_FILE]\"\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\Python3\\python.exe\" \\\n \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" \\\n run-internal \\\n \"[SKILL_DIR]/tests/test-syntax.sps\"\n```\n\n### Backup Method (No Splash)\n\n通过 `stats.com`（控制台版）调用 .spj 文件，完全无闪屏：\n\n```bash\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.com\" -production silent -nologo \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n`stats.com` 控制台版纯后台运行，绝无闪屏。\n\n最后备选（可能有闪屏）： `stats.exe -production silent -nologo`。\n\nCall .spj file via `stats.exe -production`. This method may display splash screen.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[STATS_EXE_PATH]\" -production \"[SPJ_FILE]\" silent -nologo\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe\" \\\n -production \\\n \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n## Test Files\n\n- `test-syntax.sps` — SPSS 语法文件，生成测试数据并保存\n- `test-job.spj` — SPSS 生产作业文件（备用方式使用）\n\n## Expected Results\n\n1. **无闪屏** — 运行时不显示 SPSS GUI 窗口\n2. **输出文件生成** — 生成 `test-data.sav` 文件\n3. **数据正确** — `test-data.sav` 包含 5 条记录，id 和 score 两列\n\n## Verification Method\n\n```bash\n# 检查输出文件是否生成\nls -la \"[SKILL_DIR]/test-data.sav\"\n\n# 读取 .sav 文件内容（需要 pyreadstat）\npython -c \"\nimport pyreadstat\ndf, meta = pyreadstat.read_sav('[SKILL_DIR]/test-data.sav')\nprint(df)\n\"\n```\n\n## Cleanup\n\n测试会写入 `test-data.sav`。测试完成后删除该文件即可清除所有磁盘副作用 / The test writes `test-data.sav`; delete it after the test to remove all disk side effects:\n\n```bash\nrm -f \"[SKILL_DIR]/test-data.sav\"\n```\n\n## Notes\n\n1. SPSS 26 内置 Python 3.4，不支持 f-string，所有字符串格式化必须用 `%s` 或 `.format()`\n2. 确保输出路径有写权限\n3. 如果测试失败，检查 SPSS 安装路径是否正确\n\nFile v2.7.1:_meta.json\n\n{\n \"ownerId\": \"kn7amqq1jv28skb63wavr6shah89jsm5\",\n \"slug\": \"statsoft-cli\",\n \"version\": \"2.7.1\",\n \"publishedAt\": 1784695337904\n}\n\nFile v2.7.1:references/command-examples.md\n\n# Command Invocation Examples\n\n> This document contains CLI command invocation examples for each statistical software package.\n\n---\n\n## Table of Contents\n\n1. [R](#r)\n2. [SPSS](#spss)\n3. [Stata](#stata)\n4. [SAS](#sas)\n5. [JMP](#jmp)\n6. [GraphPad Prism](#graphpad)\n7. [Stat/Transfer](#stattranfer)\n8. [Other software](#others)\n9. [JAGS](#jags)\n10. [SHAZAM](#shazam)\n11. [OxMetrics](#oxmetrics)\n12. [TSP](#tsp)\n13. [Tanagra](#tanagra)\n14. [Orange](#orange)\n15. [H2O.ai](#h2o)\n16. [GenStat](#genstat)\n17. [Rattle](#rattle)\n18. [OpenBUGS](#openbugs)\n19. [LIMDEP](#limdep)\n20. [NLOGIT](#nlogit)\n21. [Microfit](#microfit)\n\n---\n\n## R\n\n### Basic run\n\n```bash\n# Run R script\nRscript --vanilla \"script.R\"\n\n# Use R CMD BATCH (generates .Rout file)\nR CMD BATCH \"script.R\" \"output.Rout\"\n```\n\n### Package installation (requires explicit user confirmation before network download/install)\n\n```bash\n# Downloads from CRAN and modifies the local R environment; requires explicit user confirmation before running — do not install without it\nRscript -e \"install.packages('pkg', repos='https://cran.r-project.org')\"\n```\n\n### Batch script template\n\n```r\n# script.R\noptions(warn=-1)\nlibrary(dplyr)\n\ndata <- read.csv(\"data.csv\", fileEncoding=\"UTF-8\")\nresult <- lm(y ~ x1 + x2, data=data)\nsummary(result)\n\nwrite.csv(result$coefficients, \"results.csv\", row.names=FALSE)\nsave(result, file=\"results.RData\")\n```\n\n### Common scenarios\n\n```bash\n# Read SPSS .sav file\nRscript -e \"library(haven); df <- read_sav('data.sav'); print(head(df))\"\n\n# Generate HTML report\nRscript -e \"rmarkdown::render('report.Rmd', output_file='report.html')\"\n\n# Large data processing\nRscript -e \"library(arrow); df <- read_parquet('big_data.parquet'); print(dim(df))\"\n```\n\n---\n\n## SPSS\n\n### 🎯 Usage Recommendation\n\n> **For daily complex syntax runs** → **use Approach 1** (`stats.com` + `.spj`, foolproof)\n>\n> **Approach 2** (internal Python driver) **can only run pure analysis syntax** and **must not contain** the following commands:\n> - ❌ `OUTPUT SAVE`\n> - ❌ `OUTPUT EXPORT` / `OUTPUT DISPLAY`\n> - ❌ `HOST COMMAND`\n> - ❌ `XDATA` / `XSAVE` (when OUTPUT objects are involved)\n>\n> — When unsure whether a command involves OUTPUT/SAVE, use Approach 1 (`.spj`) for safety.\n\n---\n\n### ⭐ Preferred approach (completely splash-free)\n\nRun directly through the SPSS built-in Python `spss` module:\n\n```bash\n# Invoke via spss_helper.py\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\Python3\\python.exe\" \\\n \"C:\\path\\to\\statsoft-cli\\windows-only\\SPSS\\spss_helper.py\" \\\n run-internal \"C:\\path\\to\\syntax.sps\"\n```\n\n**Call chain**:\n```\nAI Agent (Bash tool)\n → python.exe spss_helper.py run-internal \n → subprocess.run([stats_python_path, helper_script], creationflags=0x08000000)\n → SPSS runs in background (zero window)\n```\n\n### Fallback approach\n\nRun the .spj file via `stats.com` (console version, completely splash-free):\n\n```bash\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\stats.com\" -production silent -nologo \"job.spj\"\n```\n\nOr use `stats.exe` (GUI version, may show a splash screen):\n\n```bash\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\stats.exe\" -production \"job.spj\" silent -nologo\n```\n\n### .spj file XML structure\n\n```xml\n\n\n \n \n \n\n```\n\n**Key**: the `` element must not be omitted, otherwise a NullPointerException is thrown.\n\n### Automated Python script (completely GUI-free)\n\n```pyt...","readmeExcerpt":"Skill: statsoft-cli Owner: medstatstar Summary: 跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation. Tags: Initial Release:1.2.0, latest:2.8.2 Version history: ","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"# 通过 spss_helper.py 运行\n\"[SPSS_PYTHON_PATH]\" \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" run-internal \"[SPS_FILE]\"\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\Python3\\python.exe\" \\\n \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" \\\n run-internal \\\n \"[SKILL_DIR]/tests/test-syntax.sps\""},{"language":"bash","snippet":"# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.com\" -production silent -nologo \"[SKILL_DIR]/tests/test-job.spj\""},{"language":"bash","snippet":"# 通过 spss_helper.py 运行\n\"[STATS_EXE_PATH]\" -production \"[SPJ_FILE]\" silent -nologo\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe\" \\\n -production \\\n \"[SKILL_DIR]/tests/test-job.spj\""},{"language":"bash","snippet":"# 检查输出文件是否生成\nls -la \"[SKILL_DIR]/test-data.sav\"\n\n# 读取 .sav 文件内容（需要 pyreadstat）\npython -c \"\nimport pyreadstat\ndf, meta = pyreadstat.read_sav('[SKILL_DIR]/test-data.sav')\nprint(df)\n\""},{"language":"bash","snippet":"rm -f \"[SKILL_DIR]/test-data.sav\""},{"language":"bash","snippet":"# Run R script\nRscript --vanilla \"script.R\"\n\n# Use R CMD BATCH (generates .Rout file)\nR CMD BATCH \"script.R\" \"output.Rout\""}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: statsoft-cli\nslug: statsoft-cli\ndisplayName: 统计软件接入助手 / Statsoft-CLI\ncn_name: 统计软件接入助手\nversion: \"2.8.2\"\nsummary: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。\"\nlicense: MIT\ndescription: \"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation.\"\ntriggers:\n - \"SPSS\"\n - \"SPSS Statistics\"\n - \"R命令行\"\n - \"Stata\"\n - \"SAS\"\n - \"统计软件\"\n - \"连接统计软件\"\n - \"statsoft-cli\"\n - \"connect statistical software\"\nrequired_commands: [python, bash, powershell]\nmetadata:\n {\n \"openclaw\": { \"emoji\": \"🛠️\", \"icon\": \"assets/icon.svg\" },\n \"authors\": [\"medstatstar\", \"phoe-zip\"],\n \"contributors\": [\"medstatstar\", \"phoe-zip\"],\n \"version\": \"2.8.2\",\n \"license\": \"MIT\",\n \"tags\": [\"Statistical Software\", \"CLI\", \"R\", \"SPSS\", \"Stata\", \"SAS\", \"Bayesian\", \"Machine Learning\", \"Econometrics\", \"SEM\", \"Data Mining\"],\n \"homepage\": \"https://github.com/medstatstar/statsoft-cli\",\n \"repository\": \"https://github.com/medstatstar/statsoft-cli\"\n }\npermissions:\n scope: \"user-space-only\"\n network: \"off\"\n network_note: \"Offline by default; only CRAN / Anaconda repo access for local dependency install, requires explicit confirmation.\"\n filesystem: \"read-only to its own files; writes only config.json under skill root with explicit opt-in\"\n data: \"no external data transmission\"\n---\n\n## Language\n\nPick the README that matches your language for human-readable, language-specific guides:\n\n- **English guide** → [README.md](https://github.com/medstatstar/statsoft-cli/blob/main/README.md)\n- **中文指南** → [README_zh-CN.md](https://github.com/medstatstar/statsoft-cli/blob/main/README_zh-CN.md)\n\nThis skill responds in the user's current input language (Chinese or English) and auto-detects / switches accordingly. The runtime scripts embed a locale check (`$script:isZH` in PowerShell, `SCRIPT_LANG` in Bash) so all user-facing prompts switch to Chinese on a `zh-*` UI culture and to English otherwise. Code comments and documentation are English-only.\n\nThe SKILL.md body, `references/*.md`, and `ADDITIONAL_SOFTWARE.md` are English-only and agent-facing; runtime command prompts switch to Chinese / English by locale. For end-to-end walkthroughs, examples, and troubleshooting in your language, open the README above.\n\n## Overview\n\nActivates historical code assets locked in statistical software (syntax, scripts, projects) and wires them into AI workflows via automated detection, configuration, and execution.\n\n## Core Functions\n\nCovers 34+ statistical / data-science packages, auto-routed by platform; non-Windows auto-hides incompatible software:\n\n- **Cross-platform (Win / Mac / Linux, CLI)**: R, Stata, SAS, CmdStan, GenStat, Gretl, H2O.ai, JAGS, Julia, KNIME, Mathematica, Matlab, O"},{"path":"README.md","content":"# statsoft-cli\n\n[🇨🇳 中文 (Chinese)](./README_zh-CN.md) | [🇬🇧 English (Current)](#)\n\n

\n \"statsoft-cli\n
\n\n> **Cross-platform statistical software CLI integration for your AI Agent**\n>\n> You don't need to learn each tool's CLI — just tell the assistant which statistical software you want to use in plain language, and it detects, configures, and runs them inside your AI workflow. Covers 34+ packages (R, Stata, SAS, SPSS, Python, Bayesian, ML…), bilingual (Chinese / English). By default it only **detects** — it never writes config or runs anything risky without your explicit go-ahead.\n\n---\n\n## 1. How to Use It in a Chat (the Core)\n\nstatsoft-cli is a **conversational skill**: you simply name the tool and the action in natural language — no commands to memorize. As a WorkBuddy skill it **auto-loads with no extra installation**.\n\n> **Quick start:** just name a tool and an action — *\"Connect SPSS 26\"*, *\"Convert data.sav to data.dta\"* — and the assistant detects, configures, and (with your OK) runs it. **It will not push you into a long menu:** a clear request acts immediately; a routing menu only appears when you're undecided (see Examples 4–5).\n\nBelow are real conversational examples ordered from simple to advanced. Each shows **\"You say\"** and a sketch of **\"The assistant replies\"**, plus how to actually trigger the real action.\n\n### Example 1 · Connect a single tool (most common)\n**You say:**\n> Connect SPSS 26\n\n**Assistant replies (sketch):**\n> Scanning for SPSS Statistics… Found it at `C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe` (v26).\n> Detected only — I did not change config.json. To save this, say \"save it\" or set `STATSOFT_AUTO_WRITE` to `1`.\n\n**📌 No menu forced (simple path):** because this is a *simple* request (a named tool + action), the assistant detects and reports directly — no scan/routing menu pops up (see the Clarification Gate in SKILL.md).\n\n**📌 Trigger the real action:** By default only detection runs (fail-closed). To persist the result, say **\"save the config\"** / **\"yes, write it\"** at the prompt, or set `STATSOFT_AUTO_WRITE` to `1`. Execution of syntax / binaries also needs explicit confirmation.\n\n### Example 2 · Run a syntax / convert data\n**You say:**\n> Convert data.sav to data.dta\n\n**Assistant replies (sketch):**\n> I'll use Stat/Transfer for that. Here is the planned command (dry-run shown). Confirm and I'll run it.\n\n### Example 3 · Multi-software workflow\n**You say:**\n> In one session, use R for modeling and SPSS for descriptive stats\n\n### Example 4 · Not sure what's installed (Complex menu)\n**You say:**\n> Set up my statistics tools, but I'm not sure which are installed or which versions I have\n\n**Assistant replies (sketch):**\n> Two ways to proceed — here's a menu:\n> **① How should I find your tools?**\n> - (a) Auto-scan my machine (~30s on Windows) — finds everything\n> - (b) I'll specify the paths myself (faster if you have ≤3)\n>"},{"path":"tests/README.md","content":"# SPSS Splash-free Call Test / SPSS 无闪屏调用测试\n\n## Test Purpose\n\n验证 SPSS 无闪屏调用方式是否正常工作。\n\nVerify that the SPSS splash-free call method works correctly.\n\n> ⚠️ **副作用提示 / Side effects**：运行本测试会**执行第三方 SPSS 二进制**，并在磁盘上**写入文件** `test-data.sav`（约 5 条记录）。这是测试的预期产物，仅供手动执行；请勿在自动化流程中静默运行。测试完成后请参见文末「清理 / Cleanup」删除该文件。\n>\n> Running this test **executes the third-party SPSS binary** and **writes a file** `test-data.sav` (~5 rows) to disk. This is an expected artifact of a manually-run test — do not run it silently in automation. See \"Cleanup\" at the end to remove it afterward.\n\n## Test Method\n\n### Preferred Method (Completely Splash-free)\n\n使用 SPSS 内置 Python 的 `spss` 模块直接运行语法，不调用 `stats.exe`，完全无 GUI。\n\nUse SPSS built-in Python's `spss` module to run syntax directly, without calling `stats.exe`, completely GUI-free.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[SPSS_PYTHON_PATH]\" \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" run-internal \"[SPS_FILE]\"\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\Python3\\python.exe\" \\\n \"[SKILL_DIR]/windows-only/SPSS/spss_helper.py\" \\\n run-internal \\\n \"[SKILL_DIR]/tests/test-syntax.sps\"\n```\n\n### Backup Method (No Splash)\n\n通过 `stats.com`（控制台版）调用 .spj 文件，完全无闪屏：\n\n```bash\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.com\" -production silent -nologo \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n`stats.com` 控制台版纯后台运行，绝无闪屏。\n\n最后备选（可能有闪屏）： `stats.exe -production silent -nologo`。\n\nCall .spj file via `stats.exe -production`. This method may display splash screen.\n\n```bash\n# 通过 spss_helper.py 运行\n\"[STATS_EXE_PATH]\" -production \"[SPJ_FILE]\" silent -nologo\n\n# 示例\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\26\\stats.exe\" \\\n -production \\\n \"[SKILL_DIR]/tests/test-job.spj\"\n```\n\n## Test Files\n\n- `test-syntax.sps` — SPSS 语法文件，生成测试数据并保存\n- `test-job.spj` — SPSS 生产作业文件（备用方式使用）\n\n## Expected Results\n\n1. **无闪屏** — 运行时不显示 SPSS GUI 窗口\n2. **输出文件生成** — 生成 `test-data.sav` 文件\n3. **数据正确** — `test-data.sav` 包含 5 条记录，id 和 score 两列\n\n## Verification Method\n\n```bash\n# 检查输出文件是否生成\nls -la \"[SKILL_DIR]/test-data.sav\"\n\n# 读取 .sav 文件内容（需要 pyreadstat）\npython -c \"\nimport pyreadstat\ndf, meta = pyreadstat.read_sav('[SKILL_DIR]/test-data.sav')\nprint(df)\n\"\n```\n\n## Cleanup\n\n测试会写入 `test-data.sav`。测试完成后删除该文件即可清除所有磁盘副作用 / The test writes `test-data.sav`; delete it after the test to remove all disk side effects:\n\n```bash\nrm -f \"[SKILL_DIR]/test-data.sav\"\n```\n\n## Notes\n\n1. SPSS 26 内置 Python 3.4，不支持 f-string，所有字符串格式化必须用 `%s` 或 `.format()`\n2. 确保输出路径有写权限\n3. 如果测试失败，检查 SPSS 安装路径是否正确"},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn7amqq1jv28skb63wavr6shah89jsm5\",\n \"slug\": \"statsoft-cli\",\n \"version\": \"2.8.2\",\n \"publishedAt\": 1785672882418\n}"},{"path":"references/command-examples.md","content":"# Command Invocation Examples\n\n> This document contains CLI command invocation examples for each statistical software package.\n\n---\n\n## Table of Contents\n\n1. [R](#r)\n2. [SPSS](#spss)\n3. [Stata](#stata)\n4. [SAS](#sas)\n5. [JMP](#jmp)\n6. [GraphPad Prism](#graphpad)\n7. [Stat/Transfer](#stattranfer)\n8. [Other software](#others)\n9. [JAGS](#jags)\n10. [SHAZAM](#shazam)\n11. [OxMetrics](#oxmetrics)\n12. [TSP](#tsp)\n13. [Tanagra](#tanagra)\n14. [Orange](#orange)\n15. [H2O.ai](#h2o)\n16. [GenStat](#genstat)\n17. [Rattle](#rattle)\n18. [OpenBUGS](#openbugs)\n19. [LIMDEP](#limdep)\n20. [NLOGIT](#nlogit)\n21. [Microfit](#microfit)\n\n---\n\n## R\n\n### Basic run\n\n```bash\n# Run R script\nRscript --vanilla \"script.R\"\n\n# Use R CMD BATCH (generates .Rout file)\nR CMD BATCH \"script.R\" \"output.Rout\"\n```\n\n### Package installation (requires explicit user confirmation before network download/install)\n\n```bash\n# Downloads from CRAN and modifies the local R environment; requires explicit user confirmation before running — do not install without it\nRscript -e \"install.packages('pkg', repos='https://cran.r-project.org')\"\n```\n\n### Batch script template\n\n```r\n# script.R\noptions(warn=-1)\nlibrary(dplyr)\n\ndata <- read.csv(\"data.csv\", fileEncoding=\"UTF-8\")\nresult <- lm(y ~ x1 + x2, data=data)\nsummary(result)\n\nwrite.csv(result$coefficients, \"results.csv\", row.names=FALSE)\nsave(result, file=\"results.RData\")\n```\n\n### Common scenarios\n\n```bash\n# Read SPSS .sav file\nRscript -e \"library(haven); df <- read_sav('data.sav'); print(head(df))\"\n\n# Generate HTML report\nRscript -e \"rmarkdown::render('report.Rmd', output_file='report.html')\"\n\n# Large data processing\nRscript -e \"library(arrow); df <- read_parquet('big_data.parquet'); print(dim(df))\"\n```\n\n---\n\n## SPSS\n\n### 🎯 Usage Recommendation\n\n> **For daily complex syntax runs** → **use Approach 1** (`stats.com` + `.spj`, foolproof)\n>\n> **Approach 2** (internal Python driver) **can only run pure analysis syntax** and **must not contain** the following commands:\n> - ❌ `OUTPUT SAVE`\n> - ❌ `OUTPUT EXPORT` / `OUTPUT DISPLAY`\n> - ❌ `HOST COMMAND`\n> - ❌ `XDATA` / `XSAVE` (when OUTPUT objects are involved)\n>\n> — When unsure whether a command involves OUTPUT/SAVE, use Approach 1 (`.spj`) for safety.\n\n---\n\n### ⭐ Preferred approach (completely splash-free)\n\nRun directly through the SPSS built-in Python `spss` module:\n\n```bash\n# Invoke via spss_helper.py\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\Python3\\python.exe\" \\\n \"C:\\path\\to\\statsoft-cli\\windows-only\\SPSS\\spss_helper.py\" \\\n run-internal \"C:\\path\\to\\syntax.sps\"\n```\n\n**Call chain**:\n```\nAI Agent (Bash tool)\n → python.exe spss_helper.py run-internal \n → subprocess.run([stats_python_path, helper_script], creationflags=0x08000000)\n → SPSS runs in background (zero window)\n```\n\n### Fallback approach\n\nRun the .spj file via `stats.com` (console version, completely splash-free):\n\n```bash\n\"C:\\Program Files\\IBM\\SPSS\\Statistics\\XX\\stats.com\" -production silent -nologo \"job.spj\"\n```\n\nOr use `stats.exe` "}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation. Skill: statsoft-cli Owner: medstatstar Summary: 跨平台统计软件 CLI 集成，面向 AI Agent；覆盖 34+ 款软件（R/Stata/SAS/SPSS/Python/贝叶斯/ML等），双语。核心价值：激活历史代码资产，用于 AI 工作流自动化。 / Cross-platform statistical software CLI integration for AI Agent; 34+ packages (R/Stata/SAS/SPSS/Python/Bayesian/ML, etc.), bilingual. Core value: activating historical code assets for AI workflow automation. 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