[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6N2MPMPCD8BN63M07EW0QSX":3,"skill-same:01M6N2MPMPCD8BN63M07EW0QSX":92},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":22,"publishedAt":43,"linkOnly":44,"markdownContent":45,"markdownBody":46,"frontMatter":47,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M6N2MPMPCD8BN63M07EW0QSX","skill-evaluator",null,"Evaluate Clawdbot skills for quality, reliability, and publish-readiness using a multi-framework rubric (ISO 25010, OpenSSF, Shneiderman, agent-specific heuristics). Use when asked to review, audit, evaluate, score, or assess a skill before publishing, or when checking skill quality. Runs automated structural checks and guides manual assessment across 25 criteria.","Kernel8901\u002Fai-agent-skills-classification","Kernel8901","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F72647553?v=4","01M6KV388J2H5PNC8D8P940BJD","01M6KV38CS5B3AY63RKZB410YM",7,"MIT","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002FSKILL.md",[17],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"skill evaluator","evaluator","structural","evaluate","for","manual","multi","assess","guides","readiness","iso","review","across","clawdbot","publishing","reliability","use","heuristics","publish","assessment","2026-11-10 10:12:30",false,"---\nname: skill-evaluator\ndescription: Evaluate Clawdbot skills for quality, reliability, and publish-readiness using a multi-framework rubric (ISO 25010, OpenSSF, Shneiderman, agent-specific heuristics). Use when asked to review, audit, evaluate, score, or assess a skill before publishing, or when checking skill quality. Runs automated structural checks and guides manual assessment across 25 criteria.\n---\n\n# Skill Evaluator\n\nEvaluate skills across 25 criteria using a hybrid automated + manual approach.\n\n## Quick Start\n\n### 1. Run automated checks\n\n```bash\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill --json    # machine-readable\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill --verbose  # show all details\n```\n\nChecks: file structure, frontmatter, description quality, script syntax, dependency audit, credential scan, env var documentation.\n\n### 2. Manual assessment\n\nUse the rubric at [references\u002Frubric.md](references\u002Frubric.md) to score 25 criteria across 8 categories (0–4 each, 100 total). Each criterion has concrete descriptions per score level.\n\n### 3. Write the evaluation\n\nCopy [assets\u002FEVAL-TEMPLATE.md](assets\u002FEVAL-TEMPLATE.md) to the skill directory as `EVAL.md`. Fill in automated results + manual scores.\n\n## Evaluation Process\n\n1. **Run `eval-skill.py`** — get the automated structural score\n2. **Read the skill's SKILL.md** — understand what it does\n3. **Read\u002Fskim the scripts** — assess code quality, error handling, testability\n4. **Score each manual criterion** using [references\u002Frubric.md](references\u002Frubric.md) — concrete criteria per level\n5. **Prioritize findings** as P0 (blocks publishing) \u002F P1 (should fix) \u002F P2 (nice to have)\n6. **Write EVAL.md** in the skill directory with scores + findings\n\n## Categories (8 categories, 25 criteria)\n\n| # | Category | Source Framework | Criteria |\n|---|----------|-----------------|----------|\n| 1 | Functional Suitability | ISO 25010 | Completeness, Correctness, Appropriateness |\n| 2 | Reliability | ISO 25010 | Fault Tolerance, Error Reporting, Recoverability |\n| 3 | Performance \u002F Context | ISO 25010 + Agent | Token Cost, Execution Efficiency |\n| 4 | Usability — AI Agent | Shneiderman, Gerhardt-Powals | Learnability, Consistency, Feedback, Error Prevention |\n| 5 | Usability — Human | Tognazzini, Norman | Discoverability, Forgiveness |\n| 6 | Security | ISO 25010 + OpenSSF | Credentials, Input Validation, Data Safety |\n| 7 | Maintainability | ISO 25010 | Modularity, Modifiability, Testability |\n| 8 | Agent-Specific | Novel | Trigger Precision, Progressive Disclosure, Composability, Idempotency, Escape Hatches |\n\n## Interpreting Scores\n\n| Range | Verdict | Action |\n|-------|---------|--------|\n| 90–100 | Excellent | Publish confidently |\n| 80–89 | Good | Publishable, note known issues |\n| 70–79 | Acceptable | Fix P0s before publishing |\n| 60–69 | Needs Work | Fix P0+P1 before publishing |\n| \u003C60 | Not Ready | Significant rework needed |\n\n## Deeper Security Scanning\n\nThis evaluator covers security basics (credentials, input validation, data safety) but for thorough security audits of skills under development, consider [SkillLens](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fskilllens) (`npx skilllens scan \u003Cpath>`). It checks for exfiltration, code execution, persistence, privilege bypass, and prompt injection — complementary to the quality focus here.\n\n## Dependencies\n\n- Python 3.6+ (for eval-skill.py)\n- PyYAML (`pip install pyyaml`) — for frontmatter parsing in automated checks\n","# Skill Evaluator\n\nEvaluate skills across 25 criteria using a hybrid automated + manual approach.\n\n## Quick Start\n\n### 1. Run automated checks\n\n```bash\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill --json    # machine-readable\npython3 scripts\u002Feval-skill.py \u002Fpath\u002Fto\u002Fskill --verbose  # show all details\n```\n\nChecks: file structure, frontmatter, description quality, script syntax, dependency audit, credential scan, env var documentation.\n\n### 2. Manual assessment\n\nUse the rubric at [references\u002Frubric.md](references\u002Frubric.md) to score 25 criteria across 8 categories (0–4 each, 100 total). Each criterion has concrete descriptions per score level.\n\n### 3. Write the evaluation\n\nCopy [assets\u002FEVAL-TEMPLATE.md](assets\u002FEVAL-TEMPLATE.md) to the skill directory as `EVAL.md`. Fill in automated results + manual scores.\n\n## Evaluation Process\n\n1. **Run `eval-skill.py`** — get the automated structural score\n2. **Read the skill's SKILL.md** — understand what it does\n3. **Read\u002Fskim the scripts** — assess code quality, error handling, testability\n4. **Score each manual criterion** using [references\u002Frubric.md](references\u002Frubric.md) — concrete criteria per level\n5. **Prioritize findings** as P0 (blocks publishing) \u002F P1 (should fix) \u002F P2 (nice to have)\n6. **Write EVAL.md** in the skill directory with scores + findings\n\n## Categories (8 categories, 25 criteria)\n\n| # | Category | Source Framework | Criteria |\n|---|----------|-----------------|----------|\n| 1 | Functional Suitability | ISO 25010 | Completeness, Correctness, Appropriateness |\n| 2 | Reliability | ISO 25010 | Fault Tolerance, Error Reporting, Recoverability |\n| 3 | Performance \u002F Context | ISO 25010 + Agent | Token Cost, Execution Efficiency |\n| 4 | Usability — AI Agent | Shneiderman, Gerhardt-Powals | Learnability, Consistency, Feedback, Error Prevention |\n| 5 | Usability — Human | Tognazzini, Norman | Discoverability, Forgiveness |\n| 6 | Security | ISO 25010 + OpenSSF | Credentials, Input Validation, Data Safety |\n| 7 | Maintainability | ISO 25010 | Modularity, Modifiability, Testability |\n| 8 | Agent-Specific | Novel | Trigger Precision, Progressive Disclosure, Composability, Idempotency, Escape Hatches |\n\n## Interpreting Scores\n\n| Range | Verdict | Action |\n|-------|---------|--------|\n| 90–100 | Excellent | Publish confidently |\n| 80–89 | Good | Publishable, note known issues |\n| 70–79 | Acceptable | Fix P0s before publishing |\n| 60–69 | Needs Work | Fix P0+P1 before publishing |\n| \u003C60 | Not Ready | Significant rework needed |\n\n## Deeper Security Scanning\n\nThis evaluator covers security basics (credentials, input validation, data safety) but for thorough security audits of skills under development, consider [SkillLens](https:\u002F\u002Fwww.npmjs.com\u002Fpackage\u002Fskilllens) (`npx skilllens scan \u003Cpath>`). It checks for exfiltration, code execution, persistence, privilege bypass, and prompt injection — complementary to the quality focus here.\n\n## Dependencies\n\n- Python 3.6+ (for eval-skill.py)\n- PyYAML (`pip install pyyaml`) — for frontmatter parsing in automated checks\n",{"name":5,"description":7},"main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","人工智能与大型语言模型\u002Fskill-evaluator",1,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification","https:\u002F\u002Fgithub.com\u002FKernel8901","a little little little dobe in life but science geek","2026-04-05 16:43:56",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill skill-evaluator",{"tool":62,"command":63},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill skill-evaluator",{"tool":65,"command":66},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill skill-evaluator","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002FSKILL.md",true,[70,76,82,86],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"_meta.json","REFERENCE","参考文档",282,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002F_meta.json",{"path":77,"resourceType":78,"resourceTypeDesc":79,"sizeBytes":80,"sourceHtmlUrl":81},"assets\u002FEVAL-TEMPLATE.md","ASSET","资产文件",1367,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002Fassets\u002FEVAL-TEMPLATE.md",{"path":83,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Frubric.md",11370,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002Freferences\u002Frubric.md",{"path":87,"resourceType":88,"resourceTypeDesc":89,"sizeBytes":90,"sourceHtmlUrl":91},"scripts\u002Feval-skill.py","SCRIPT","脚本",23689,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fskill-evaluator\u002Fscripts\u002Feval-skill.py",[93,116,147,158,168,197],{"skillNo":94,"name":95,"nameZh":6,"description":96,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":99,"publishedAt":43},"01M6Q5R6WZ06RRB9RQTW54B34B","zyfai","Earn yield on any Ethereum wallet on Base, Arbitrum, and Plasma. Use when a user wants passive DeFi yield on their funds. Deploys a non-custodial subaccount (Safe) linked to their EOA, enables automated yield optimization, and lets them deposit\u002Fwithdraw anytime.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzyfai-sdk\u002FSKILL.md",[],[95,100,101,102,103,104,39,105,106,107,108,109,110,111,112,113,114,115],"safe","ethereum","defi","Optimization","user","Wallet","base","deposit","withdraw","yield","arbitrum","non-custodial","passive","defi yield","earn","yield optimization",{"skillNo":117,"name":118,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":130,"publishedAt":43},"01M6Q5R337B5JSNER4P4YS03TN","zerion-api","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api\u002FSKILL.md",[121,124,125],{"categoryNo":122,"categoryName":123,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[131,132,133,134,135,136,137,102,138,105,139,140,141,142,143,35,144,145,146],"api","zerion api","zerion","MCP","mcp server","server","blockchain","transactions","crypto wallet","crypto","evm","solana","query","positions","token","prices",{"skillNo":148,"name":149,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":150,"categories":151,"keywords":155,"publishedAt":43},"01M6Q5QZFYTDAZMZ27BN5VZXAR","zerion-api-skill","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-skill\u002FSKILL.md",[152,153,154],{"categoryNo":122,"categoryName":123,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},[131,156,157,132,133,134,135,136,137,102,138,105,140,141,142,143,35,144,145,146],"api skill","zerion api skill",{"skillNo":159,"name":160,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":166,"publishedAt":43},"01M6Q5QW17QW98RA3FE45E4RD8","zerion-api-mcp","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-mcp\u002FSKILL.md",[163,164,165],{"categoryNo":122,"categoryName":123,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},[134,131,167,132,133,135,136,102,138,105,139,140,141,142,143,35,144,145,146],"zerion api mcp",{"skillNo":169,"name":170,"nameZh":6,"description":171,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":172,"categories":173,"keywords":177,"publishedAt":43},"01M6Q5QQYZB7A501BDEQWKGSJT","yahoo-finance-forex","Fetches real-time FOREX news and market data from Yahoo Finance for major currency pairs (EUR\u002FUSD, GBP\u002FUSD, USD\u002FJPY, etc.). Analyzes sentiment and provides trading context.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-forex\u002FSKILL.md",[174],{"categoryNo":175,"categoryName":176,"taxonomyType":128,"taxonomyTypeDesc":129},"01JBSEEDCAT000000000000040","财务",[178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,27],"finance","yahoo finance","forex","yahoo","yahoo finance forex","github","https","sentiment","real-time","python3","install","Market","usd","news","time","currency","gbp","pip","market data",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":204,"publishedAt":43},"01M6Q5QM6VS84WZVM7BKXXPF32","yahoo-finance","This skill should be used when the user asks to \"get stock prices\", \"check stock quotes\", \"look up earnings\", \"get financial data\", \"find trending stocks\", or needs stock market data from Yahoo Finance.","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fyahoo-finance-cli\u002FSKILL.md",[203],{"categoryNo":175,"categoryName":176,"taxonomyType":128,"taxonomyTypeDesc":129},[178,179,181,205,206,207,208,209,210,189,211,212,213,214,215,216,217,218,146,196],"cli","homebrew","find","check","brew","up","local","get","stock","link","trending","sf","quotes","ln"]