[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G97C4P2C1XDW20WTNCF05Q":3,"skill-same:01M6G97C4P2C1XDW20WTNCF05Q":76},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":6,"ownerDescription":60,"updatedAt":61,"install":62,"resources":75},"01M6G97C4P2C1XDW20WTNCF05Q","scorecard-review",null,"Review service maturity scorecards and compliance using Harness IDP via MCP. Check production readiness, security, and documentation scores. Use when user says \"scorecard\", \"service maturity\", \"production readiness\", \"compliance score\", or asks about service health scores.","zapabob\u002FSkills","zapabob","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130830376?v=4","01M6DBMYZAGRTFQDSQYW3W764P","峯岸 亮","01M6DBMZ3GKDSJ01NZ9XTZD7JD",2,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002F74\u002F7415a025bd13e34d303099b289ea119762d82cb22510b11a4263ffda725507c5\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"review","scorecard review","scorecard","use","MCP","security","about","via","readiness","service","scorecards","production readiness","documentation","user","check","health","Production","compliance","server","harness","2026-11-10 10:12:30",false,"---\r\nname: scorecard-review\r\ndescription: Review service maturity scorecards and compliance using Harness IDP via MCP. Check production readiness, security, and documentation scores. Use when user says \"scorecard\", \"service maturity\", \"production readiness\", \"compliance score\", or asks about service health scores.\r\nmetadata:\r\n  author: Harness\r\n  version: 2.0.0\r\n  mcp-server: harness-mcp-v2\r\nlicense: Apache-2.0\r\ncompatibility: Requires Harness MCP v2 server (harness-mcp-v2)\r\n---\r\n\r\n# Scorecard Review\r\n\r\nReview service maturity and compliance scorecards using Harness Internal Developer Portal (IDP) via MCP.\r\n\r\n## Instructions\r\n\r\n### Step 1: List Catalog Entities\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_entity\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n### Step 2: Get Entity Details\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"idp_entity\"\r\n  resource_id: \"\u003Centity_id>\"\r\n```\r\n\r\n### Step 3: Get Scorecard Scores\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_score\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\nGet specific entity score:\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"idp_score\"\r\n  resource_id: \"\u003Centity_id>\"\r\n```\r\n\r\n### Step 4: Check Documentation\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_tech_doc\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n### Step 5: Review Workflows\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_workflow\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n## Common Scorecard Categories\r\n\r\n- **Production Readiness** - CI\u002FCD, monitoring, alerting, runbooks\r\n- **Security Compliance** - Vulnerability scanning, secrets management, access control\r\n- **Documentation** - API docs, architecture diagrams, runbooks\r\n- **Operational Excellence** - SLOs, incident response, on-call\r\n- **Developer Experience** - Build times, test coverage, onboarding\r\n\r\n## Report Format\r\n\r\n```\r\n## Service Scorecard Report\r\n\r\n**Service:** \u003Cname>\r\n**Overall Score:** X\u002F100\r\n\r\n### Category Scores\r\n| Category | Score | Status |\r\n|----------|-------|--------|\r\n| Production Readiness | 85\u002F100 | Pass |\r\n| Security | 70\u002F100 | Needs Work |\r\n| Documentation | 45\u002F100 | Failing |\r\n| Operations | 90\u002F100 | Pass |\r\n\r\n### Failing Checks\r\n1. Missing API documentation\r\n2. No SBOM generation configured\r\n3. Test coverage below 80%\r\n\r\n### Improvement Actions\r\n1. Add API docs to \u002Fdocs endpoint\r\n2. Enable SBOM in CI pipeline\r\n3. Increase test coverage to 80%+\r\n```\r\n\r\n## IDP Resource Types\r\n\r\n| Resource Type | Operations | Description |\r\n|--------------|-----------|-------------|\r\n| `idp_entity` | list, get | Catalog entities |\r\n| `idp_score` | list, get | Scorecard scores |\r\n| `idp_tech_doc` | list, get | Technical docs |\r\n| `idp_workflow` | list, get | IDP workflows |\r\n\r\n## Examples\r\n\r\n- \"How is api-gateway doing on scorecards?\" - Get idp_score for entity\r\n- \"Which services are failing production readiness?\" - List idp_score, filter by failing\r\n- \"Help me improve checkout-service score\" - Get score, identify failing checks, suggest fixes\r\n- \"Show all services below 80% compliance\" - List and filter idp_score\r\n\r\n## Performance Notes\r\n\r\n- Analyze all scorecard checks before recommending improvements. Do not skip failing checks.\r\n- Cross-reference failing checks with the service's actual configuration and documentation.\r\n- Prioritize recommendations by impact — focus on checks that affect production readiness first.\r\n\r\n## Troubleshooting\r\n\r\n### No Scores Available\r\n- Verify scorecards are configured in IDP settings\r\n- Check entity is registered in the catalog\r\n- Ensure data sources (CI\u002FCD, monitoring) are connected\r\n\r\n### Scores Not Updating\r\n- Check integration sync status\r\n- Verify data source connectivity\r\n- Review scorecard rule configuration\r\n","# Scorecard Review\r\n\r\nReview service maturity and compliance scorecards using Harness Internal Developer Portal (IDP) via MCP.\r\n\r\n## Instructions\r\n\r\n### Step 1: List Catalog Entities\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_entity\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n### Step 2: Get Entity Details\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"idp_entity\"\r\n  resource_id: \"\u003Centity_id>\"\r\n```\r\n\r\n### Step 3: Get Scorecard Scores\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_score\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\nGet specific entity score:\r\n\r\n```\r\nCall MCP tool: harness_get\r\nParameters:\r\n  resource_type: \"idp_score\"\r\n  resource_id: \"\u003Centity_id>\"\r\n```\r\n\r\n### Step 4: Check Documentation\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_tech_doc\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n### Step 5: Review Workflows\r\n\r\n```\r\nCall MCP tool: harness_list\r\nParameters:\r\n  resource_type: \"idp_workflow\"\r\n  org_id: \"\u003Corganization>\"\r\n  project_id: \"\u003Cproject>\"\r\n```\r\n\r\n## Common Scorecard Categories\r\n\r\n- **Production Readiness** - CI\u002FCD, monitoring, alerting, runbooks\r\n- **Security Compliance** - Vulnerability scanning, secrets management, access control\r\n- **Documentation** - API docs, architecture diagrams, runbooks\r\n- **Operational Excellence** - SLOs, incident response, on-call\r\n- **Developer Experience** - Build times, test coverage, onboarding\r\n\r\n## Report Format\r\n\r\n```\r\n## Service Scorecard Report\r\n\r\n**Service:** \u003Cname>\r\n**Overall Score:** X\u002F100\r\n\r\n### Category Scores\r\n| Category | Score | Status |\r\n|----------|-------|--------|\r\n| Production Readiness | 85\u002F100 | Pass |\r\n| Security | 70\u002F100 | Needs Work |\r\n| Documentation | 45\u002F100 | Failing |\r\n| Operations | 90\u002F100 | Pass |\r\n\r\n### Failing Checks\r\n1. Missing API documentation\r\n2. No SBOM generation configured\r\n3. Test coverage below 80%\r\n\r\n### Improvement Actions\r\n1. Add API docs to \u002Fdocs endpoint\r\n2. Enable SBOM in CI pipeline\r\n3. Increase test coverage to 80%+\r\n```\r\n\r\n## IDP Resource Types\r\n\r\n| Resource Type | Operations | Description |\r\n|--------------|-----------|-------------|\r\n| `idp_entity` | list, get | Catalog entities |\r\n| `idp_score` | list, get | Scorecard scores |\r\n| `idp_tech_doc` | list, get | Technical docs |\r\n| `idp_workflow` | list, get | IDP workflows |\r\n\r\n## Examples\r\n\r\n- \"How is api-gateway doing on scorecards?\" - Get idp_score for entity\r\n- \"Which services are failing production readiness?\" - List idp_score, filter by failing\r\n- \"Help me improve checkout-service score\" - Get score, identify failing checks, suggest fixes\r\n- \"Show all services below 80% compliance\" - List and filter idp_score\r\n\r\n## Performance Notes\r\n\r\n- Analyze all scorecard checks before recommending improvements. Do not skip failing checks.\r\n- Cross-reference failing checks with the service's actual configuration and documentation.\r\n- Prioritize recommendations by impact — focus on checks that affect production readiness first.\r\n\r\n## Troubleshooting\r\n\r\n### No Scores Available\r\n- Verify scorecards are configured in IDP settings\r\n- Check entity is registered in the catalog\r\n- Ensure data sources (CI\u002FCD, monitoring) are connected\r\n\r\n### Scores Not Updating\r\n- Check integration sync status\r\n- Verify data source connectivity\r\n- Review scorecard rule configuration\r\n",{"name":5,"license":15,"metadata":49,"description":7,"compatibility":53},{"author":50,"version":51,"mcp-server":52},"Harness","2.0.0","harness-mcp-v2","Requires Harness MCP v2 server (harness-mcp-v2)","main","0d1434f89f4bc6b07e9d272accd8c1013768820f","archive\u002Fskill-md-reviewed\u002Fsha256\u002F74\u002F7415a025bd13e34d303099b289ea119762d82cb22510b11a4263ffda725507c5",0,"https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills","https:\u002F\u002Fgithub.com\u002Fzapabob","The Open University of JAPAN　2019-now\r\n\r\nTokyo University of Science　2007-2010","2026-10-26 16:29:01",{"source":8,"skillName":5,"commands":63,"prompt":73,"zipAvailable":74},[64,67,70],{"tool":65,"command":66},"npx","npx skills add zapabob\u002FSkills --skill scorecard-review",{"tool":68,"command":69},"bunx","bunx skills add zapabob\u002FSkills --skill scorecard-review",{"tool":71,"command":72},"pnpm","pnpm dlx skills add zapabob\u002FSkills --skill scorecard-review","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Farchive\u002Fskill-md-reviewed\u002Fsha256\u002F74\u002F7415a025bd13e34d303099b289ea119762d82cb22510b11a4263ffda725507c5\u002FSKILL.md",true,[],[77,111,144,170,197,214],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":82,"categories":83,"keywords":93,"publishedAt":44},"01M6GJTE1GESGGF9K028Y7753E","xurl","X\u002FTwitter via xurl CLI: post, search, DM, media, v2 API.","MIT","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fxurl\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[84,87,88],{"categoryNo":85,"categoryName":86,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[79,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,54,109,31,110],"openclaw","macos","cli","github","linux","windows","official","search","https","social-media","api","Media","hermes","hermes agent","twitter","social","post",{"skillNo":112,"name":113,"nameZh":6,"description":114,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":128,"publishedAt":44},"01M6GJT8S1PXQ8WPXT1HSNBWH2","writing-plans","Write implementation plans: bite-sized tasks, paths, code.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwriting-plans\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[117,120,123,124,125],{"categoryNo":118,"categoryName":119,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":121,"categoryName":122,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},{"categoryNo":126,"categoryName":127,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000036","内容创作者",[129,130,131,132,95,24,98,133,99,36,134,135,136,137,138,139,140,141,142,143],"writing","writing plans","plans","design","workflow","tasks","development","code","planning","code-review","subagent","write","superpowers","paths","test-driven-development",{"skillNo":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":153,"publishedAt":44},"01M6GJST0H5X7WHBJ3BZK0DVKH","whisper","OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwhisper\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[150],{"categoryNo":151,"categoryName":152,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",[146,95,98,154,155,156,157,158,159,160,161,162,27,163,164,165,166,167,168,169],"openai","speech","multimodal","Transformers","ASR","Audio","text","model","speech recognition","general","multilingual","translation","english","identification","processing","Audio Processing",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":174,"categories":175,"keywords":179,"publishedAt":44},"01M6GJSMRQ8EETZTYMG72P70EA","weights-and-biases","W&B: log ML experiments, sweeps, model registry, dashboards.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fweights-and-biases\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[176],{"categoryNo":177,"categoryName":178,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000013","分析与可视化",[180,95,181,182,99,183,184,185,186,187,188,161,189,190,191,192,193,194,195,196],"weights and biases","tensorflow","experiments","pytorch","visualization","registry","real-time","tuning","dashboards","experiment","log","time","Experiment Tracking","Model Registry","Hyperparameter Tuning","WandB","Real-Time Visualization",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":201,"categories":202,"keywords":204,"publishedAt":44},"01M6GJS19KDPRY112JTR326S06","watchers","Poll RSS, JSON APIs, and GitHub with watermark dedup.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fwatchers\u002Fvariants\u002Fhermes-agent-optional\u002FSKILL.md",[203],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[199,95,205,97,98,206,207,208,209,210,211,106,107,212,213],"terminal","automation","http","monitoring","cron","json","rss","devops","with",{"skillNo":215,"name":216,"nameZh":6,"description":217,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":81,"licenseFileUrl":6,"sourceHtmlUrl":218,"categories":219,"keywords":222,"publishedAt":44},"01M6GJRHJD2A6Q830SWF9W48BC","serving-llms-vllm","vLLM: high-throughput LLM serving, OpenAI API, quantization.","https:\u002F\u002Fgithub.com\u002Fzapabob\u002FSkills\u002Fblob\u002Fmain\u002Fregistry\u002Fskills\u002Fvllm\u002Fvariants\u002Fhermes-agent\u002FSKILL.md",[220,221],{"categoryNo":85,"categoryName":86,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},[223,224,225,98,226,154,227,228,229,157,40,104,230,231,232,233,234,235,236,237],"llms","vLLM","serving llms vllm","research","openai api","tensor","Inference Serving","llm serving","High Throughput","PagedAttention","Continuous Batching","Quantization","Tensor Parallelism","high-throughput","throughput"]