{"id":"f6887f74-8d61-421a-a01e-c94589f6beb3","entityType":"agent","slug":"clawhub-cellcog-pair-programming-cellcog","name":"Pair Programming","canonicalUrl":"https://www.xpersona.co/agent/clawhub-cellcog-pair-programming-cellcog","canonicalPath":"/agent/clawhub-cellcog-pair-programming-cellcog","generatedAt":"2026-10-10T03:52:00.963Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":null},"description":"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents. Skill: Pair Programming Owner: cellcog Summary: AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents. Tags: latest:1.0.15 Version history: v1.0.15 | 2026-08-24T02:04:08.111Z | user Content updated. v1.0.14 | 2026-08-24T01:48:46.580Z | user Content updated. v1.0.13 | 2026-","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 2.3K downloads reported by the source. Last updated 10/9/2026.","installCommand":"clawhub skill install s176q1btpn094ats9b4f9hgfwx83knpk:pair-programming-cellcog","sourceUrl":"https://clawhub.ai/cellcog/pair-programming-cellcog","homepage":"https://clawhub.ai/cellcog/skills/pair-programming-cellcog","primaryLinks":[{"label":"View on ClawHub","url":"https://clawhub.ai/cellcog/pair-programming-cellcog","kind":"source"},{"label":"Homepage","url":"https://clawhub.ai/cellcog/skills/pair-programming-cellcog","kind":"homepage"}],"safetyScore":84,"overallRank":62,"popularityScore":67,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full developm"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[],"verifiedCount":0,"selfDeclaredCount":1,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile"}},"adoption":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":null},"stars":null,"forks":null,"downloads":2270,"packageName":null,"latestVersion":"1.0.15","tractionLabel":"2.3K downloads"},"release":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":null},"lastUpdatedAt":"2026-10-09T16:50:49.937Z","lastCrawledAt":"2026-10-09T16:50:49.937Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-10T16:50:49.937Z","lastVerifiedAt":null,"highlights":[{"version":"1.0.15","createdAt":"2026-08-24T02:04:08.111Z","changelog":"Content updated.","fileCount":3,"zipByteSize":4573},{"version":"1.0.14","createdAt":"2026-08-24T01:48:46.580Z","changelog":"Content updated.","fileCount":3,"zipByteSize":4474},{"version":"1.0.13","createdAt":"2026-08-03T06:08:48.003Z","changelog":"Content updated.","fileCount":3,"zipByteSize":4246},{"version":"1.0.12","createdAt":"2026-08-02T22:05:42.834Z","changelog":"Display title updated.","fileCount":3,"zipByteSize":4127},{"version":"1.0.11","createdAt":"2026-07-22T15:57:46.391Z","changelog":"- Skill renamed from \"cowork-cog\" to \"pair-programming-cellcog\". - Documentation updated with new skill name and consistent terminology. - Suggestion to install \"coding-agent-cellcog\" instead of \"code-cog\" for enhanced coding. - Removed the file \"skill-card.md\".","fileCount":3,"zipByteSize":4070},{"version":"1.0.10","createdAt":"2026-04-23T06:18:40.809Z","changelog":"- Added Windows to the list of supported operating systems in metadata. - Declared new requirements in metadata: Python 3 (bin) and CELLCOG_API_KEY (environment variable). - No changes to functional usage or documentation content beyond metadata updates.","fileCount":3,"zipByteSize":4216},{"version":"1.0.9","createdAt":"2026-04-14T17:31:56.750Z","changelog":"- Shortened and clarified the skill description for easier understanding. - Simplified usage instructions, highlighting the distinction between OpenClaw and other agents. - Improved wording and formatting for consistency and readability across all sections. - No code or functionality changes; documentation only.","fileCount":2,"zipByteSize":2957},{"version":"1.0.8","createdAt":"2026-04-13T01:00:31.300Z","changelog":"- Expanded the usage instructions to clarify agent provider options for different environments (OpenClaw, Cursor, Claude Code, Codex, etc.). - Updated the skill description for improved clarity on features: now emphasizes AI pair programming, remote coding, and full development workflows. - Minor edits in documentation for precision, including additional example code and clearer guidance for multi-agent support. - No changes to code or dependencies; documentation (SKILL.md) update only.","fileCount":2,"zipByteSize":2990}]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install s176q1btpn094ats9b4f9hgfwx83knpk:pair-programming-cellcog","setupComplexity":"low","setupSteps":["Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.","Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data."],"contract":{"contractStatus":"missing","authModes":[],"requires":[],"forbidden":[],"supportsMcp":false,"supportsA2a":false,"supportsStreaming":false,"inputSchemaRef":null,"outputSchemaRef":null,"dataRegion":null,"contractUpdatedAt":null,"sourceUpdatedAt":null,"freshnessSeconds":null},"invocationGuide":{"preferredApi":{"snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"CLAWHUB","generatedAt":"2026-10-10T03:52:00.962Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-cellcog-pair-programming-cellcog/trust"}},"reliability":{"evidence":{"source":"runtime-metrics","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No trust, reliability, or runtime telemetry is available."},"trust":{"status":"unavailable","handshakeStatus":"UNKNOWN","verificationFreshnessHours":null,"reputationScore":null,"p95LatencyMs":null,"successRate30d":null,"fallbackRate":null,"attempts30d":null,"trustUpdatedAt":null,"trustConfidence":"unknown","sourceUpdatedAt":null,"freshnessSeconds":null},"decisionGuardrails":{"doNotUseIf":["Contract metadata is missing or unavailable for deterministic execution."],"safeUseWhen":[],"riskFlags":["missing_or_unavailable_contract","trust_data_unavailable","schema_references_missing"],"operationalConfidence":"low"},"executionMetrics":{"observedLatencyMsP50":null,"observedLatencyMsP95":null,"estimatedCostUsd":null,"uptime30d":null,"rateLimitRpm":null,"rateLimitBurst":null,"lastVerifiedAt":null,"verificationSource":null},"runtimeMetrics":{"successRate":null,"avgLatencyMs":null,"avgCostUsd":null,"hallucinationRate":null,"retryRate":null,"disputeRate":null,"p50Latency":null,"p95Latency":null,"lastUpdated":null}},"benchmarks":{"evidence":{"source":"no-benchmark-data","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No benchmark suites or observed failure patterns are available."},"suites":[],"failurePatterns":[]},"artifacts":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"high","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":null},"readme":"Skill: Pair Programming\n\nOwner: cellcog\n\nSummary: AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\n\nTags: latest:1.0.15\n\nVersion history:\n\nv1.0.15 | 2026-08-24T02:04:08.111Z | user\n\nContent updated.\n\nv1.0.14 | 2026-08-24T01:48:46.580Z | user\n\nContent updated.\n\nv1.0.13 | 2026-08-03T06:08:48.003Z | user\n\nContent updated.\n\nv1.0.12 | 2026-08-02T22:05:42.834Z | user\n\nDisplay title updated.\n\nv1.0.11 | 2026-07-22T15:57:46.391Z | auto\n\n- Skill renamed from \"cowork-cog\" to \"pair-programming-cellcog\".\n- Documentation updated with new skill name and consistent terminology.\n- Suggestion to install \"coding-agent-cellcog\" instead of \"code-cog\" for enhanced coding.\n- Removed the file \"skill-card.md\".\n\nv1.0.10 | 2026-04-23T06:18:40.809Z | auto\n\n- Added Windows to the list of supported operating systems in metadata.\n- Declared new requirements in metadata: Python 3 (bin) and CELLCOG_API_KEY (environment variable).\n- No changes to functional usage or documentation content beyond metadata updates.\n\nv1.0.9 | 2026-04-14T17:31:56.750Z | auto\n\n- Shortened and clarified the skill description for easier understanding.\n- Simplified usage instructions, highlighting the distinction between OpenClaw and other agents.\n- Improved wording and formatting for consistency and readability across all sections.\n- No code or functionality changes; documentation only.\n\nv1.0.8 | 2026-04-13T01:00:31.300Z | auto\n\n- Expanded the usage instructions to clarify agent provider options for different environments (OpenClaw, Cursor, Claude Code, Codex, etc.).\n- Updated the skill description for improved clarity on features: now emphasizes AI pair programming, remote coding, and full development workflows.\n- Minor edits in documentation for precision, including additional example code and clearer guidance for multi-agent support.\n- No changes to code or dependencies; documentation (SKILL.md) update only.\n\nv1.0.7 | 2026-04-12T23:35:07.819Z | auto\n\ncowork-cog 1.0.7\n\n- SKILL.md has been streamlined and reworded for clarity and conciseness.\n- \"cellcog mothership skill\" language updated to simply \"cellcog skill.\"\n- Added a \"How to Use\" section with concise agent usage code examples.\n- Referenced https://cellcog.ai for SDK documentation instead of in-document duplication.\n- Reduced and clarified introductory and usage sections for easier onboarding.\n- No changes to code or functionality—documentation update only.\n\nv1.0.6 | 2026-04-11T05:52:30.462Z | auto\n\n- Updated usage instructions in SKILL.md to initialize the client with agent_provider=\"openclaw\" (was agent_name).\n- No functional code or logic changes; documentation only.\n\nv1.0.5 | 2026-04-11T02:58:42.587Z | auto\n\n- Added agent_name=\"openclaw\" parameter to the CellCogClient instantiation example in the Quick Start section.\n- No other user-facing changes. Documentation updated to clarify agent usage in code samples.\n\nv1.0.4 | 2026-04-08T05:57:43.910Z | auto\n\n- Major documentation update: SKILL.md rewritten for clarity and depth.\n- Expanded \"Quick Start\" and setup instructions, including specific CLI/SDK code examples.\n- Added \"Why Co-work?\" and \"What You Can Build\" sections to highlight benefits and use cases.\n- Included comprehensive desktop app installation steps, error recovery, and security notes.\n- Improved chat mode explanations for more effective agent workflow setup.\n- General content refresh for easier onboarding and developer understanding.\n\nv1.0.3 | 2026-04-06T05:06:55.727Z | auto\n\n- Updated documentation to clarify Cowork Cog as the first agent-focused co-work platform, emphasizing direct machine access for agents.\n- Improved explanation of CellCog Desktop’s capabilities: terminal, file system, development environment, and auto-approval for agent workflows.\n- Simplified setup instructions and highlighted key parameters for enabling coworking.\n- Enhanced security model section with bullet points for easy reference.\n- Added clear references to related skills (code-cog, project-cog) for expanded functionality.\n\nv1.0.2 | 2026-04-03T01:43:09.654Z | auto\n\n- Added clarity on co-work chat initiation, now distinguishing OpenClaw agent usage with notify_session_key vs other agents.\n- Updated \"Quick Start\" example to reflect agent-specific parameters and usage guidance.\n- No functional or API changes; documentation only.\n\nv1.0.1 | 2026-04-03T00:07:34.308Z | auto\n\n- Clarified language in setup and quick start sections for easier onboarding.\n- Updated code examples for conciseness and added blocking behavior in `create_chat`.\n- Added references to the cellcog mothership skill for full SDK API documentation.\n- Improved instructions for co-work chat mode and task labeling.\n- Minor wording and formatting enhancements for better readability.\n\nv1.0.0 | 2026-04-02T03:33:34.776Z | auto\n\ncowork-cog 1.0.0\n\n- Initial release.\n- Allows CellCog agents to code, debug, refactor, and build directly on your local machine via CellCog Desktop.\n- Fully autonomous: all commands are auto-approved for agents, no manual approval required.\n- Supports co-working workflows for file access, terminal usage, and full development tasks.\n- Built-in security: blocks access to sensitive files, redacts credentials, and scopes sessions to project directories.\n- Compatible with macOS and Linux. Requires the cellcog skill and CellCog Desktop app.\n\nArchive index:\n\nArchive v1.0.15: 3 files, 4573 bytes\n\nFiles: skill-card.md (2512b), SKILL.md (6896b), _meta.json (144b)\n\nFile v1.0.15:SKILL.md\n\n---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill cellcog\n\n# OpenClaw\nopenclaw skills install @cellcog/cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Choosing Mode & Tier\n\n**Use `chat_mode=\"agent\", chat_tier=\"max\"` for all coding work** — code needs the deepest reasoning tier. The SDK applies `\"max\"` automatically whenever `enable_cowork=True`, so co-work sessions get it even without an explicit tier.\n\n`\"agent core\"` is a legacy name that still works forever (the server maps it to Agent max), but new code should pass `chat_mode=\"agent\", chat_tier=\"max\"`.\n\nAgent Team (`chat_mode=\"team\"`) is reserved for deep research — use it only when the task IS research that happens to involve code.\n\nBrowse rides Co-work: `create_chat(enable_browse=True, browser_profile_id=...)` lets the agent drive the user's real Chrome alongside the terminal (profiles discoverable via `client.get_browser_status()`; enabling Browse auto-enables Co-work server-side).\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `coding-agent-cellcog`:\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill coding-agent-cellcog\n\n# OpenClaw\nopenclaw skills install @cellcog/coding-agent-cellcog\n```\n\nFile v1.0.15:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.15\",\n \"publishedAt\": 1787537048111\n}\n\nFile v1.0.15:skill-card.md\n\n## Description:\n\nAI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows - auto-approved for agents.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and external users use this skill to delegate coding tasks to CellCog cloud agents through CellCog Desktop on a local project workspace. It supports code generation, debugging, refactoring, DevOps setup, data pipelines, and documentation workflows.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: CellCog cloud agents may operate on the user's machine with broad unattended access to local commands, files, installation steps, and possibly a real browser profile.\n\nMitigation: Install only when this remote co-work behavior is intended; use a disposable or tightly scoped project directory and avoid workspaces containing secrets or sensitive repositories.\n\nRisk: Auto-approved commands and desktop installation or lifecycle commands can make local changes without per-command human prompts.\n\nMitigation: Manually verify desktop installer details, versions, signatures, and commands before running them, and confirm that the CellCog Desktop connection is expected.\n\nRisk: Browser-profile access could expose personal sessions or sensitive browsing data.\n\nMitigation: Do not grant access to personal browser profiles; use a dedicated profile when browse-enabled workflows are required.\n\n## Reference(s):\n\n- [CellCog homepage](https://cellcog.ai)\n- [ClawHub skill page](https://clawhub.ai/cellcog/skills/pair-programming-cellcog)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance]\n\n**Output Format:** [Markdown guidance with Python and bash code blocks plus JSON-producing CLI command guidance]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; supports darwin, linux, and windows; uses CellCog Desktop for local command and file operations.]\n\n## Skill Version(s):\n\n1.0.15 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.14: 3 files, 4474 bytes\n\nFiles: skill-card.md (2356b), SKILL.md (6862b), _meta.json (144b)\n\nFile v1.0.14:SKILL.md\n\n---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill cellcog\n\n# OpenClaw\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Choosing Mode & Tier\n\n**Use `chat_mode=\"agent\", chat_tier=\"max\"` for all coding work** — code needs the deepest reasoning tier. The SDK applies `\"max\"` automatically whenever `enable_cowork=True`, so co-work sessions get it even without an explicit tier.\n\n`\"agent core\"` is a legacy name that still works forever (the server maps it to Agent max), but new code should pass `chat_mode=\"agent\", chat_tier=\"max\"`.\n\nAgent Team (`chat_mode=\"team\"`) is reserved for deep research — use it only when the task IS research that happens to involve code.\n\nBrowse rides Co-work: `create_chat(enable_browse=True, browser_profile_id=...)` lets the agent drive the user's real Chrome alongside the terminal (profiles discoverable via `client.get_browser_status()`; enabling Browse auto-enables Co-work server-side).\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `coding-agent-cellcog`:\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill coding-agent-cellcog\n\n# OpenClaw\nclawhub install coding-agent-cellcog\n```\n\nFile v1.0.14:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.14\",\n \"publishedAt\": 1787536126580\n}\n\nFile v1.0.14:skill-card.md\n\n## Description:\n\nAI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows - auto-approved for agents.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and coding agents use this skill to delegate code, debugging, refactoring, DevOps, data pipeline, and documentation tasks to CellCog agents operating through CellCog Desktop on a scoped local project directory.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: CellCog cloud agents can run auto-approved commands and perform file operations through CellCog Desktop on the user's machine.\n\nMitigation: Use a narrowly chosen working directory and avoid granting access to directories containing secrets, private databases, production credentials, or personal browser/session data.\n\nRisk: The skill requires a CellCog API key and may configure CellCog Desktop on the local machine.\n\nMitigation: Verify how CellCog Desktop stores API keys, review status and logs, and stop or remove the desktop app when it is no longer needed.\n\nRisk: Browser and local execution capabilities can expose sensitive local context if enabled for broad projects or profiles.\n\nMitigation: Use per-chat working-directory scoping, confirm path limits and output redaction, and enable browser access only for profiles appropriate to the task.\n\n## Reference(s):\n\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/pair-programming-cellcog)\n- [CellCog](https://cellcog.ai)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration]\n\n**Output Format:** [Markdown with inline code and shell command examples]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include SDK calls, desktop CLI commands, configuration steps, and guidance for scoped local project work.]\n\n## Skill Version(s):\n\n1.0.14 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.13: 3 files, 4246 bytes\n\nFiles: skill-card.md (2193b), SKILL.md (6634b), _meta.json (144b)\n\nFile v1.0.13:SKILL.md\n\n---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill cellcog\n\n# OpenClaw\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `coding-agent-cellcog`:\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill coding-agent-cellcog\n\n# OpenClaw\nclawhub install coding-agent-cellcog\n```\n\nFile v1.0.13:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.13\",\n \"publishedAt\": 1785737328003\n}\n\nFile v1.0.13:skill-card.md\n\n## Description:
\nAI pair programming powered by CellCog Desktop for coding, debugging, refactoring, and building directly on a user's machine with terminal access and file operations.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[cellcog](https://clawhub.ai/user/cellcog)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nDevelopers and engineering agents use this skill to delegate coding, debugging, refactoring, DevOps, data pipeline, and documentation work to CellCog cloud agents connected through CellCog Desktop in a chosen local project directory.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: CellCog cloud agents can run local commands and read or write project files autonomously through CellCog Desktop.
\nMitigation: Use a narrowly chosen project directory and avoid workspaces that contain secrets, production data, customer logs, private databases, or unrelated repositories.
\nRisk: Auto-approved command execution may expose sensitive local context or make unintended project changes.
\nMitigation: Review CellCog's desktop, privacy, and retention behavior before enabling co-work, and keep each chat scoped to the intended working directory.
\n\n\n## Reference(s):
\n- [CellCog SDK and Desktop Documentation](https://cellcog.ai)
\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/pair-programming-cellcog)
\n\n\n## Skill Output:
\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance]
\n**Output Format:** [Markdown guidance with Python and shell command examples]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; ClawHub metadata lists darwin, linux, and windows support.]
\n\n## Skill Version(s):
\n1.0.13 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.12: 3 files, 4127 bytes\n\nFiles: skill-card.md (2054b), SKILL.md (6413b), _meta.json (144b)\n\nFile v1.0.12:SKILL.md\n\n---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `coding-agent-cellcog`:\n```bash\nclawhub install coding-agent-cellcog\n```\n\nFile v1.0.12:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.12\",\n \"publishedAt\": 1785708342834\n}\n\nFile v1.0.12:skill-card.md\n\n## Description:
\nAI pair programming powered by CellCog Desktop, enabling agents to code, debug, refactor, run terminal commands, and work with files on the user's machine.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[cellcog](https://clawhub.ai/user/cellcog)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nDevelopers and engineers use this skill to delegate coding, debugging, refactoring, documentation, DevOps, and data-pipeline tasks to CellCog agents that can operate in a selected local working directory.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: CellCog cloud agents can run commands and edit files inside the selected project without per-command approval.
\nMitigation: Use a dedicated working directory, avoid sensitive projects and secrets, and keep backups or version control available before delegating work.
\nRisk: The skill requires a CellCog API key and desktop bridge to enable local agent operations.
\nMitigation: Limit API-key exposure, verify desktop connection state before use, and scope each chat to the intended working directory.
\n\n\n## Reference(s):
\n- [ClawHub Skill Page](https://clawhub.ai/cellcog/skills/pair-programming-cellcog)
\n- [CellCog](https://cellcog.ai)
\n\n\n## Skill Output:
\n**Output Type(s):** [Guidance, Code, Shell commands, Configuration]
\n**Output Format:** [Markdown with Python and bash code blocks]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [May include SDK calls, desktop setup commands, and task delegation instructions for a selected working directory.]
\n\n## Skill Version(s):
\n1.0.12 (source: server release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.11: 3 files, 4070 bytes\n\nFiles: skill-card.md (1974b), SKILL.md (6413b), _meta.json (144b)\n\nFile v1.0.11:SKILL.md\n\n---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `coding-agent-cellcog`:\n```bash\nclawhub install coding-agent-cellcog\n```\n\nFile v1.0.11:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.11\",\n \"publishedAt\": 1784735866391\n}\n\nFile v1.0.11:skill-card.md\n\n## Description:
\nAI pair programming powered by CellCog Desktop for coding, debugging, refactoring, and building on a user's machine with terminal and file operations.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[nitishgargiitd](https://clawhub.ai/user/nitishgargiitd)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nDevelopers use this skill to delegate coding, debugging, refactoring, documentation, and development setup tasks to CellCog cloud agents connected to a chosen local working directory through CellCog Desktop.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: CellCog cloud agents may run commands and edit files automatically in the selected working directory without per-command approval.
\nMitigation: Use a disposable or tightly scoped project directory, avoid locations with secrets or production credentials, and review generated changes before relying on them.
\n\n\n## Reference(s):
\n- [ClawHub Skill Page](https://clawhub.ai/nitishgargiitd/skills/pair-programming-cellcog)
\n- [CellCog](https://cellcog.ai)
\n- [CellCog Desktop Co-work](https://cellcog.ai/cowork)
\n\n\n## Skill Output:
\n**Output Type(s):** [Code, Shell commands, Configuration, Guidance]
\n**Output Format:** [Markdown guidance with Python and shell command examples]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; outputs may instruct agents to use CellCog Desktop co-work against a selected local working directory.]
\n\n## Skill Version(s):
\n1.0.11 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.10: 3 files, 4216 bytes\n\nFiles: skill-card.md (2294b), SKILL.md (6369b), _meta.json (144b)\n\nFile v1.0.10:SKILL.md\n\n---\nname: cowork-cog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Cowork Cog — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `code-cog`:\n```bash\nclawhub install code-cog\n```\n\nFile v1.0.10:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.10\",\n \"publishedAt\": 1776925120809\n}\n\nFile v1.0.10:skill-card.md\n\n## Description:
\nAI pair programming powered by CellCog Desktop for code, debugging, refactoring, and local development workflows on the user's machine.
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[nitishgargiitd](https://clawhub.ai/user/nitishgargiitd)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nDevelopers and engineering teams use this skill to delegate coding, debugging, refactoring, DevOps, data pipeline, and documentation tasks to CellCog agents working within a local project directory.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: Cloud agents can receive auto-approved terminal and file-operation access on the user's machine.
\nMitigation: Install only for intentional local co-work use, scope each session to a dedicated project directory, keep work under version control, and narrow or disable auto-approval when autonomous writes or commands are not acceptable.
\nRisk: The skill requires CELLCOG_API_KEY and CellCog Desktop, which can expose local development workflows to a remote coding service.
\nMitigation: Verify how the desktop app stores the API key, avoid sensitive folders, review generated changes before relying on them, and stop or disconnect CellCog Desktop when co-work access is no longer needed.
\n\n\n## Reference(s):
\n- [Cowork Cog on ClawHub](https://clawhub.ai/nitishgargiitd/cowork-cog)
\n- [CellCog](https://cellcog.ai)
\n\n\n## Skill Output:
\n**Output Type(s):** [text, markdown, code, shell commands, configuration, guidance]
\n**Output Format:** [Markdown guidance with Python and shell command examples; CellCog responses may include JSON and task results.]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Requires python3, the cellcog dependency, CELLCOG_API_KEY, and CellCog Desktop for local co-work sessions.]
\n\n## Skill Version(s):
\n1.0.10 (source: server release evidence)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
\n\nArchive v1.0.9: 2 files, 2957 bytes\n\nFiles: SKILL.md (6295b), _meta.json (143b)\n\nFile v1.0.9:SKILL.md\n\n---\nname: cowork-cog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux]\ndependencies: [cellcog]\n---\n# Cowork Cog — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `code-cog`:\n```bash\nclawhub install code-cog\n```\n\nFile v1.0.9:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.9\",\n \"publishedAt\": 1776187916750\n}\n\nArchive v1.0.8: 2 files, 2990 bytes\n\nFiles: SKILL.md (6411b), _meta.json (143b)\n\nFile v1.0.8:SKILL.md\n\n---\nname: cowork-cog\ndescription: \"CellCog on your machine. Turn any computer into CellCog's workspace — code, debug, refactor, and build directly on the user's machine. Auto-approved for agents, no manual intervention. CellCog Desktop bridge for terminal, file access, and full development workflows. AI pair programming, remote coding agent.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux]\ndependencies: [cellcog]\n---\n# Cowork Cog — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**Cursor / Claude Code / Other agents (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `code-cog`:\n```bash\nclawhub install code-cog\n```\n\nFile v1.0.8:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.8\",\n \"publishedAt\": 1776042031300\n}\n\nArchive v1.0.7: 2 files, 2918 bytes\n\nFiles: SKILL.md (6194b), _meta.json (143b)\n\nFile v1.0.7:SKILL.md\n\n---\nname: cowork-cog\ndescription: \"Powered by CellCog. CellCog on your machine. Turn any computer into CellCog's workspace — code, debug, refactor, and build directly on the user's machine. Auto-approved for agents. CellCog Desktop bridge.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux]\ndependencies: [cellcog]\n---\n# Cowork Cog — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**Cursor / Claude Code / Other agents (blocks until done):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee https://cellcog.ai for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `code-cog`:\n```bash\nclawhub install code-cog\n```\n\nFile v1.0.7:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.7\",\n \"publishedAt\": 1776036907819\n}\n\nArchive v1.0.6: 2 files, 2814 bytes\n\nFiles: SKILL.md (5588b), _meta.json (143b)\n\nFile v1.0.6:SKILL.md\n\n---\nname: cowork-cog\ndescription: \"CellCog on your machine. Turn any computer into CellCog's workspace — code, debug, refactor, and build directly on the user's machine. Auto-approved for agents, no manual intervention. CellCog Desktop bridge for terminal, file access, and full development workflows. AI pair programming, remote coding agent.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux]\ndependencies: [cellcog]\n---\n\n# Cowork Cog — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` mothership skill for SDK setup and API calls.\n\n```bash\nclawhub install cellcog\n```\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n```\n\n---\n\n## Desktop App Setup\n\nCall `client.get_desktop_download_urls()` — returns download URLs and platform-specific install commands for macOS, Windows, and Linux.\n\nAfter installation:\n```bash\ncellcog-desktop --set-api-key \ncellcog-desktop --start\n```\n\nThe agent can do all of this programmatically — no human interaction needed beyond providing the API key.\n\nAlternatively, ask your human to download CellCog Desktop from `cellcog.ai/cowork`, open it, and enter their API key.\n\n---\n\n## Desktop CLI Reference\n\nAll commands output JSON for easy agent parsing:\n\n| Command | What it does |\n|---------|-------------|\n| `cellcog-desktop --set-api-key ` | Authenticate with API key |\n| `cellcog-desktop --status` | Check connection + app state |\n| `cellcog-desktop --start` / `--stop` | App lifecycle |\n| `cellcog-desktop --logs` | Debug logs |\n\n---\n\n## Chat Mode for Co-work\n\nUse `\"agent core\"` mode for coding tasks — lightweight context focused on code, terminal, and file operations. Multimedia tools load on demand when needed.\n\n```python\nresult = client.create_chat(\n prompt=\"Your coding task\",\n chat_mode=\"agent core\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"my-task\",\n)\n```\n\n`\"agent\"` mode also works with co-work but loads all multimedia tools upfront. Use `\"agent core\"` for faster, more focused coding sessions.\n\nSee the **cellcog** mothership skill for complete SDK API reference — delivery modes, `send_message()`, timeouts, and more.\n\n---\n\n## Error Recovery\n\nIf the desktop app disconnects, CellCog auto-fails pending commands with a clear message.\n\nTo recover:\n```bash\ncellcog-desktop --stop && cellcog-desktop --start\n```\n\nThen send `continue` to the chat:\n```python\nclient.send_message(chat_id=\"abc123\", message=\"continue\")\n```\n\n---\n\n## Security\n\nEven with auto-approve, these protections are always active:\n- **Blocked paths**: `~/.ssh`, `~/.aws`, credential files are inaccessible\n- **Output redaction**: Sensitive data is automatically redacted from command output\n- **Per-chat scoping**: Each chat session is scoped to its working directory\n\n---\n\n## What You Can Build\n\nCo-work enables the full spectrum of development tasks:\n\n- **Web development** — Build React apps, APIs, landing pages\n- **Bug fixing** — Debug stack traces, fix test failures\n- **Refactoring** — Modernize codebases, improve architecture\n- **DevOps** — Set up CI/CD, Docker configs, infrastructure\n- **Data pipelines** — ETL scripts, database migrations\n- **Documentation** — Generate docs from code, README files\n\nFor the best coding experience, also install `code-cog`:\n```bash\nclawhub install code-cog\n```\n\nFile v1.0.6:_meta.json\n\n{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.6\",\n \"publishedAt\": 1775886750462\n}","readmeExcerpt":"Skill: Pair Programming Owner: cellcog Summary: AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents. Tags: latest:1.0.15 Version history: v1.0.15 | 2026-08-24T02:04:08.111Z | user Content updated. v1.0.14 | 2026-08-24T01:48:46.580Z | user Content updated. v1.0.13 | 2026-","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill cellcog\n\n# OpenClaw\nopenclaw skills install @cellcog/cellcog"},{"language":"python","snippet":"result = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)"},{"language":"python","snippet":"from cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])"},{"language":"python","snippet":"from cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info = client.get_desktop_download_urls()\n # info contains per-platform URLs + install commands\n # Run the install commands for the user's OS, then:\n # cellcog-desktop --set-api-key \n # cellcog-desktop --start\n\n# 3. Create a co-work chat\n\n# OpenClaw agents (fire-and-forget):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n notify_session_key=\"agent:main:main\", # OpenClaw only\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)\n\n# All other agents (blocks until done):\nresult = client.create_chat(\n prompt=\"Refactor the auth module to use JWT tokens\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/Users/me/project\",\n task_label=\"refactor-auth\",\n)"},{"language":"bash","snippet":"cellcog-desktop --set-api-key \ncellcog-desktop --start"},{"language":"bash","snippet":"cellcog-desktop --stop && cellcog-desktop --start"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: pair-programming-cellcog\ndescription: \"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents.\"\nauthor: CellCog\nhomepage: https://cellcog.ai\nmetadata:\n openclaw:\n emoji: \"🖥️\"\n os: [darwin, linux, windows]\n requires:\n bins: [python3]\n env: [CELLCOG_API_KEY]\ndependencies: [cellcog]\n---\n# Pair Programming — CellCog on Your Machine\n\nCo-work turns any machine into CellCog's workspace. CellCog Desktop acts as a bridge: CellCog's cloud agents coordinate with the desktop app to run commands, read files, and write code directly on the user's machine.\n\nAll commands are **auto-approved** for SDK/agent users — fully autonomous, no manual approval needed.\n\n## Prerequisites\n\nThis skill requires the `cellcog` skill for SDK setup and API calls.\n\n```bash\n# Claude Code, Cursor, Codex + 70 more agents\nnpx skills add cellcog/skills --skill cellcog\n\n# OpenClaw\nopenclaw skills install @cellcog/cellcog\n```\n\n## How to Use\n\nFor your first CellCog task in a session, read the **cellcog** skill for the full SDK reference — file handling, chat modes, timeouts, and more.\n\n**OpenClaw (fire-and-forget):**\n```python\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n notify_session_key=\"agent:main:main\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\n```\n\n**All agents except OpenClaw (blocks until done):**\n```python\nfrom cellcog import CellCogClient\nclient = CellCogClient(agent_provider=\"openclaw|cursor|claude-code|codex|...\")\nresult = client.create_chat(\n prompt=\"[your task prompt]\",\n task_label=\"my-task\",\n chat_mode=\"agent\",\n chat_tier=\"max\",\n enable_cowork=True,\n cowork_working_directory=\"/path/to/project\",\n)\nprint(result[\"message\"])\n```\n\n\n---\n\n## Why Co-work?\n\n### Your Machine as a Data Source\nYour data lives on the user's machine — project files, databases, logs, configs. Instead of uploading everything, enable co-work with a working directory and CellCog agents explore, read, and reason about the data directly. No file size limits, no upload hassle.\n\n### CellCog as Your Coding Powerhouse\nCellCog agents are among the most capable coding agents available — deep reasoning paired with real execution. Enable co-work and delegate complex coding tasks: build websites, APIs, fix bugs, refactor codebases, set up infrastructure.\n\n**CellCog itself is built using this exact co-work capability.**\n\nThink of it as a Claude Code or Cursor alternative, backed by CellCog's multi-agent depth and any-to-any engine.\n\n---\n\n## Quick Start\n\n```python\nfrom cellcog import CellCogClient\n\nclient = CellCogClient(agent_provider=\"openclaw\")\n\n# 1. Check if desktop app is connected\nstatus = client.get_desktop_status()\n\n# 2. If not connected, get install instructions\nif not status[\"connected\"]:\n info ="},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn7a96cj9q65e0bhmzahv790en80ffqm\",\n \"slug\": \"pair-programming-cellcog\",\n \"version\": \"1.0.15\",\n \"publishedAt\": 1787537048111\n}"},{"path":"skill-card.md","content":"## Description:\n\nAI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows - auto-approved for agents.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[cellcog](https://clawhub.ai/user/cellcog)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and external users use this skill to delegate coding tasks to CellCog cloud agents through CellCog Desktop on a local project workspace. It supports code generation, debugging, refactoring, DevOps setup, data pipelines, and documentation workflows.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: CellCog cloud agents may operate on the user's machine with broad unattended access to local commands, files, installation steps, and possibly a real browser profile.\n\nMitigation: Install only when this remote co-work behavior is intended; use a disposable or tightly scoped project directory and avoid workspaces containing secrets or sensitive repositories.\n\nRisk: Auto-approved commands and desktop installation or lifecycle commands can make local changes without per-command human prompts.\n\nMitigation: Manually verify desktop installer details, versions, signatures, and commands before running them, and confirm that the CellCog Desktop connection is expected.\n\nRisk: Browser-profile access could expose personal sessions or sensitive browsing data.\n\nMitigation: Do not grant access to personal browser profiles; use a dedicated profile when browse-enabled workflows are required.\n\n## Reference(s):\n\n- [CellCog homepage](https://cellcog.ai)\n- [ClawHub skill page](https://clawhub.ai/cellcog/skills/pair-programming-cellcog)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, Code, Shell commands, Configuration, Guidance]\n\n**Output Format:** [Markdown guidance with Python and bash code blocks plus JSON-producing CLI command guidance]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Requires python3 and CELLCOG_API_KEY; supports darwin, linux, and windows; uses CellCog Desktop for local command and file operations.]\n\n## Skill Version(s):\n\n1.0.15 (source: server release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents. Skill: Pair Programming Owner: cellcog Summary: AI pair programming powered by CellCog Desktop. Code, debug, refactor, and build directly on the user's machine. Terminal access, file operations, full development workflows — auto-approved for agents. Tags: latest:1.0.15 Version history: v1.0.15 | 2026-08-24T02:04:08.111Z | user Content updated. v1.0.14 | 2026-08-24T01:48:46.580Z | user Content updated. v1.0.13 | 2026-","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":1231,"uniquenessScore":50,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T16:50:49.937Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T03:52:00.963Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs","url":"https://github.com/CherryHQ/cherry-studio","homepage":"https://cherry-ai.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-11T14:38:40.986Z","createdAt":"2026-02-25T03:38:19.379Z","downloads":null},{"id":"6f6582d0-5d76-4f0f-b81d-86520247950b","entityType":"agent","canonicalPath":"/agent/copilotkit-copilotkit","slug":"copilotkit-copilotkit","name":"CopilotKit","description":"The Frontend for Agents & Generative UI. React + Angular","url":"https://github.com/CopilotKit/CopilotKit","homepage":"https://docs.copilotkit.ai","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-03-25T09:50:57.846Z","createdAt":"2026-02-25T03:39:14.617Z","downloads":null}],"links":{"hub":"/agent","source":"/agent/source/clawhub","protocols":[{"label":"OpenClaw","href":"/agent/protocol/openclew"}]}}}