{"id":"12542c5d-ca5c-4b3e-ad9d-aafb4468ceaa","entityType":"agent","slug":"clawhub-hu-xiao-tian-clean-code-styleguide","name":"编程规范指南","canonicalUrl":"https://www.xpersona.co/agent/clawhub-hu-xiao-tian-clean-code-styleguide","canonicalPath":"/agent/clawhub-hu-xiao-tian-clean-code-styleguide","generatedAt":"2026-10-11T17:43:32.328Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-11T15:45:04.405Z","emptyReason":null},"description":"Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes... Skill: 编程规范指南 Owner: hu-xiao-tian Summary: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-15T02:25:25.089Z | user Initial release of \"karpathy-guidelines\" skill. - Introduces a set of concise behavioral guidelines to reduce common coding mistakes in LLM","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 1K downloads reported by the source. Last updated 10/11/2026.","installCommand":"clawhub skill install s174yvznf559ttzx66jpwyqbcs84wfjh:clean-code-styleguide","sourceUrl":"https://clawhub.ai/hu-xiao-tian/clean-code-styleguide","homepage":"https://clawhub.ai/hu-xiao-tian/skills/clean-code-styleguide","primaryLinks":[{"label":"View on ClawHub","url":"https://clawhub.ai/hu-xiao-tian/clean-code-styleguide","kind":"source"},{"label":"Homepage","url":"https://clawhub.ai/hu-xiao-tian/skills/clean-code-styleguide","kind":"homepage"}],"safetyScore":84,"overallRank":62,"popularityScore":60,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes..."},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-11T15:45:04.405Z","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":"2026-10-11T15:45:04.405Z","emptyReason":null},"stars":null,"forks":null,"downloads":1036,"packageName":null,"latestVersion":"1.0.0","tractionLabel":"1K downloads"},"release":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T15:45:04.400Z","emptyReason":null},"lastUpdatedAt":"2026-10-11T15:45:04.405Z","lastCrawledAt":"2026-10-11T15:45:04.400Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-12T15:45:04.400Z","lastVerifiedAt":null,"highlights":[{"version":"1.0.0","createdAt":"2026-04-15T02:25:25.089Z","changelog":"Initial release of \"karpathy-guidelines\" skill. - Introduces a set of concise behavioral guidelines to reduce common coding mistakes in LLM-driven code tasks. - Emphasizes clarity of assumptions, simplicity in implementation, and making only targeted (surgical) code changes. - Promotes explicit definition of success criteria and iterative goal-driven development. - Based on publicly shared principles by Andrej Karpathy, adapted to guide coding, reviewing, or refactoring practices.","fileCount":3,"zipByteSize":2713}]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install s174yvznf559ttzx66jpwyqbcs84wfjh:clean-code-styleguide","setupComplexity":"low","setupSteps":["Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.","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-hu-xiao-tian-clean-code-styleguide/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/trust"},"curlExamples":["curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/snapshot\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/contract\"","curl -s \"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/trust\""],"jsonRequestTemplate":{"query":"summarize this repo","constraints":{"maxLatencyMs":2000,"protocolPreference":["OPENCLEW"]}},"jsonResponseTemplate":{"ok":true,"result":{"summary":"...","confidence":0.9},"meta":{"source":"CLAWHUB","generatedAt":"2026-10-11T17:43:32.327Z"}},"retryPolicy":{"maxAttempts":3,"backoffMs":[500,1500,3500],"retryableConditions":["HTTP_429","HTTP_503","NETWORK_TIMEOUT"]}},"endpoints":{"dossierUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/dossier","snapshotUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/snapshot","contractUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/contract","trustUrl":"https://www.xpersona.co/api/v1/agents/clawhub-hu-xiao-tian-clean-code-styleguide/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":"2026-10-11T15:45:04.405Z","emptyReason":null},"readme":"Skill: 编程规范指南\n\nOwner: hu-xiao-tian\n\nSummary: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes...\n\nTags: latest:1.0.0\n\nVersion history:\n\nv1.0.0 | 2026-04-15T02:25:25.089Z | user\n\nInitial release of \"karpathy-guidelines\" skill.\n\n- Introduces a set of concise behavioral guidelines to reduce common coding mistakes in LLM-driven code tasks.\n- Emphasizes clarity of assumptions, simplicity in implementation, and making only targeted (surgical) code changes.\n- Promotes explicit definition of success criteria and iterative goal-driven development.\n- Based on publicly shared principles by Andrej Karpathy, adapted to guide coding, reviewing, or refactoring practices.\n\nArchive index:\n\nArchive v1.0.0: 3 files, 2713 bytes\n\nFiles: skill-card.md (1681b), SKILL.md (2518b), _meta.json (140b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: karpathy-guidelines\ndescription: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.\nlicense: MIT\n---\n\n# Karpathy Guidelines\n\nBehavioral guidelines to reduce common LLM coding mistakes, derived from [Andrej Karpathy's observations](https://x.com/karpathy/status/2015883857489522876) on LLM coding pitfalls.\n\n**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.\n\n## 1. Think Before Coding\n\n**Don't assume. Don't hide confusion. Surface tradeoffs.**\n\nBefore implementing:\n- State your assumptions explicitly. If uncertain, ask.\n- If multiple interpretations exist, present them - don't pick silently.\n- If a simpler approach exists, say so. Push back when warranted.\n- If something is unclear, stop. Name what's confusing. Ask.\n\n## 2. Simplicity First\n\n**Minimum code that solves the problem. Nothing speculative.**\n\n- No features beyond what was asked.\n- No abstractions for single-use code.\n- No \"flexibility\" or \"configurability\" that wasn't requested.\n- No error handling for impossible scenarios.\n- If you write 200 lines and it could be 50, rewrite it.\n\nAsk yourself: \"Would a senior engineer say this is overcomplicated?\" If yes, simplify.\n\n## 3. Surgical Changes\n\n**Touch only what you must. Clean up only your own mess.**\n\nWhen editing existing code:\n- Don't \"improve\" adjacent code, comments, or formatting.\n- Don't refactor things that aren't broken.\n- Match existing style, even if you'd do it differently.\n- If you notice unrelated dead code, mention it - don't delete it.\n\nWhen your changes create orphans:\n- Remove imports/variables/functions that YOUR changes made unused.\n- Don't remove pre-existing dead code unless asked.\n\nThe test: Every changed line should trace directly to the user's request.\n\n## 4. Goal-Driven Execution\n\n**Define success criteria. Loop until verified.**\n\nTransform tasks into verifiable goals:\n- \"Add validation\" → \"Write tests for invalid inputs, then make them pass\"\n- \"Fix the bug\" → \"Write a test that reproduces it, then make it pass\"\n- \"Refactor X\" → \"Ensure tests pass before and after\"\n\nFor multi-step tasks, state a brief plan:\n```\n1. [Step] → verify: [check]\n2. [Step] → verify: [check]\n3. [Step] → verify: [check]\n```\n\nStrong success criteria let you loop independently. Weak criteria (\"make it work\") require constant clarification.\n\nFile v1.0.0:_meta.json\n\n{\n  \"ownerId\": \"kn75797k5e30kwj7y9zgx4sgv984x0mk\",\n  \"slug\": \"clean-code-styleguide\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776219925089\n}\n\nFile v1.0.0:skill-card.md\n\n## Description:\n\nBehavioral guidelines to reduce common LLM coding mistakes when writing, reviewing, or refactoring code.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[hu-xiao-tian](https://clawhub.ai/user/hu-xiao-tian)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and coding agents use this skill to keep implementation, review, and refactoring work simple, explicit, scoped, and verifiable.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill may bias agents toward slower, more explicit planning and verification across coding tasks.\n\nMitigation: Apply judgment for trivial tasks and keep planning proportional to task complexity.\n\nRisk: Guidance-only behavior can still lead to incorrect or misleading coding decisions if applied mechanically.\n\nMitigation: Review generated code and verify changes with focused tests or checks before deployment.\n\n## Reference(s):\n\n- [Andrej Karpathy observation on LLM coding pitfalls](https://x.com/karpathy/status/2015883857489522876)\n\n## Skill Output:\n\n**Output Type(s):** [guidance, markdown, code]\n\n**Output Format:** [Markdown guidance and concise text instructions]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [No executable output; the skill influences agent coding posture and review behavior.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release metadata)\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.","readmeExcerpt":"Skill: 编程规范指南 Owner: hu-xiao-tian Summary: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-15T02:25:25.089Z | user Initial release of \"karpathy-guidelines\" skill. - Introduces a set of concise behavioral guidelines to reduce common coding mistakes in LLM","codeSnippets":[],"executableExamples":[{"language":"text","snippet":"1. [Step] → verify: [check]\n2. [Step] → verify: [check]\n3. [Step] → verify: [check]"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: karpathy-guidelines\ndescription: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.\nlicense: MIT\n---\n\n# Karpathy Guidelines\n\nBehavioral guidelines to reduce common LLM coding mistakes, derived from [Andrej Karpathy's observations](https://x.com/karpathy/status/2015883857489522876) on LLM coding pitfalls.\n\n**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.\n\n## 1. Think Before Coding\n\n**Don't assume. Don't hide confusion. Surface tradeoffs.**\n\nBefore implementing:\n- State your assumptions explicitly. If uncertain, ask.\n- If multiple interpretations exist, present them - don't pick silently.\n- If a simpler approach exists, say so. Push back when warranted.\n- If something is unclear, stop. Name what's confusing. Ask.\n\n## 2. Simplicity First\n\n**Minimum code that solves the problem. Nothing speculative.**\n\n- No features beyond what was asked.\n- No abstractions for single-use code.\n- No \"flexibility\" or \"configurability\" that wasn't requested.\n- No error handling for impossible scenarios.\n- If you write 200 lines and it could be 50, rewrite it.\n\nAsk yourself: \"Would a senior engineer say this is overcomplicated?\" If yes, simplify.\n\n## 3. Surgical Changes\n\n**Touch only what you must. Clean up only your own mess.**\n\nWhen editing existing code:\n- Don't \"improve\" adjacent code, comments, or formatting.\n- Don't refactor things that aren't broken.\n- Match existing style, even if you'd do it differently.\n- If you notice unrelated dead code, mention it - don't delete it.\n\nWhen your changes create orphans:\n- Remove imports/variables/functions that YOUR changes made unused.\n- Don't remove pre-existing dead code unless asked.\n\nThe test: Every changed line should trace directly to the user's request.\n\n## 4. Goal-Driven Execution\n\n**Define success criteria. Loop until verified.**\n\nTransform tasks into verifiable goals:\n- \"Add validation\" → \"Write tests for invalid inputs, then make them pass\"\n- \"Fix the bug\" → \"Write a test that reproduces it, then make it pass\"\n- \"Refactor X\" → \"Ensure tests pass before and after\"\n\nFor multi-step tasks, state a brief plan:\n```\n1. [Step] → verify: [check]\n2. [Step] → verify: [check]\n3. [Step] → verify: [check]\n```\n\nStrong success criteria let you loop independently. Weak criteria (\"make it work\") require constant clarification."},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn75797k5e30kwj7y9zgx4sgv984x0mk\",\n  \"slug\": \"clean-code-styleguide\",\n  \"version\": \"1.0.0\",\n  \"publishedAt\": 1776219925089\n}"},{"path":"skill-card.md","content":"## Description:\n\nBehavioral guidelines to reduce common LLM coding mistakes when writing, reviewing, or refactoring code.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[hu-xiao-tian](https://clawhub.ai/user/hu-xiao-tian)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and coding agents use this skill to keep implementation, review, and refactoring work simple, explicit, scoped, and verifiable.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill may bias agents toward slower, more explicit planning and verification across coding tasks.\n\nMitigation: Apply judgment for trivial tasks and keep planning proportional to task complexity.\n\nRisk: Guidance-only behavior can still lead to incorrect or misleading coding decisions if applied mechanically.\n\nMitigation: Review generated code and verify changes with focused tests or checks before deployment.\n\n## Reference(s):\n\n- [Andrej Karpathy observation on LLM coding pitfalls](https://x.com/karpathy/status/2015883857489522876)\n\n## Skill Output:\n\n**Output Type(s):** [guidance, markdown, code]\n\n**Output Format:** [Markdown guidance and concise text instructions]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [No executable output; the skill influences agent coding posture and review behavior.]\n\n## Skill Version(s):\n\n1.0.0 (source: server release metadata)\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":"Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes... Skill: 编程规范指南 Owner: hu-xiao-tian Summary: Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes... Tags: latest:1.0.0 Version history: v1.0.0 | 2026-04-15T02:25:25.089Z | user Initial release of \"karpathy-guidelines\" skill. - Introduces a set of concise behavioral guidelines to reduce common coding mistakes in LLM","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":960,"uniquenessScore":58,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-11T15:45:04.405Z","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":"2026-10-11T15:45:04.405Z","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":"2026-10-11T17:43:32.328Z","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"}]}}}