[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M730HVTTTYD3FFB6Z2DCMP7H":3,"skill-same:01M730HVTTTYD3FFB6Z2DCMP7H":50},{"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":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":26,"commitSha":27,"skillDirectory":28,"forksCount":29,"repositoryHtmlUrl":30,"repositoryHomepageUrl":31,"ownerHtmlUrl":32,"ownerBlogUrl":33,"ownerDescription":34,"updatedAt":35,"install":36,"resources":49},"01M730HVTTTYD3FFB6Z2DCMP7H","api-connector-builder",null,"Build a new API connector or provider by matching the target repo's existing integration pattern exactly. Use when adding one more integration without inventing a second architecture.","Horonomos-laps\u002FYana-AI","Horonomos-laps","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F355299122?v=4","01M76B3QPXE88ET2SQPDPVATZT"," Horonomos-laps","01M72ZQRJPCYPSSWT4D00VJR2A",13,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fapi-connector-builder\u002FSKILL.md",[],[],"2026-11-11 15:11:14",false,"---\nname: api-connector-builder\ndescription: Build a new API connector or provider by matching the target repo's existing integration pattern exactly. Use when adding one more integration without inventing a second architecture.\norigin: ECC direct-port adaptation\nversion: \"1.0.0\"\n---\n\n# API Connector Builder\n\nUse this when the job is to add a repo-native integration surface, not just a generic HTTP client.\n\nThe point is to match the host repository's pattern:\n\n- connector layout\n- config schema\n- auth model\n- error handling\n- test style\n- registration\u002Fdiscovery wiring\n\n## When to Use\n\n- \"Build a Jira connector for this project\"\n- \"Add a Slack provider following the existing pattern\"\n- \"Create a new integration for this API\"\n- \"Build a plugin that matches the repo's connector style\"\n\n## Guardrails\n\n- do not invent a new integration architecture when the repo already has one\n- do not start from vendor docs alone; start from existing in-repo connectors first\n- do not stop at transport code if the repo expects registry wiring, tests, and docs\n- do not cargo-cult old connectors if the repo has a newer current pattern\n\n## Workflow\n\n### 1. Learn the house style\n\nInspect at least 2 existing connectors\u002Fproviders and map:\n\n- file layout\n- abstraction boundaries\n- config model\n- retry \u002F pagination conventions\n- registry hooks\n- test fixtures and naming\n\n### 2. Narrow the target integration\n\nDefine only the surface the repo actually needs:\n\n- auth flow\n- key entities\n- core read\u002Fwrite operations\n- pagination and rate limits\n- webhook or polling model\n\n### 3. Build in repo-native layers\n\nTypical slices:\n\n- config\u002Fschema\n- client\u002Ftransport\n- mapping layer\n- connector\u002Fprovider entrypoint\n- registration\n- tests\n\n### 4. Validate against the source pattern\n\nThe new connector should look obvious in the codebase, not imported from a different ecosystem.\n\n## Reference Shapes\n\n### Provider-style\n\n```text\nproviders\u002F\n  existing_provider\u002F\n    __init__.py\n    provider.py\n    config.py\n```\n\n### Connector-style\n\n```text\nintegrations\u002F\n  existing\u002F\n    client.py\n    models.py\n    connector.py\n```\n\n### TypeScript plugin-style\n\n```text\nsrc\u002Fintegrations\u002F\n  existing\u002F\n    index.ts\n    client.ts\n    types.ts\n    test.ts\n```\n\n## Quality Checklist\n\n- [ ] matches an existing in-repo integration pattern\n- [ ] config validation exists\n- [ ] auth and error handling are explicit\n- [ ] pagination\u002Fretry behavior follows repo norms\n- [ ] registry\u002Fdiscovery wiring is complete\n- [ ] tests mirror the host repo's style\n- [ ] docs\u002Fexamples are updated if expected by the repo\n\n## Related Skills\n\n- `backend-patterns`\n- `mcp-server-patterns`\n- `github-ops`\n","# API Connector Builder\n\nUse this when the job is to add a repo-native integration surface, not just a generic HTTP client.\n\nThe point is to match the host repository's pattern:\n\n- connector layout\n- config schema\n- auth model\n- error handling\n- test style\n- registration\u002Fdiscovery wiring\n\n## When to Use\n\n- \"Build a Jira connector for this project\"\n- \"Add a Slack provider following the existing pattern\"\n- \"Create a new integration for this API\"\n- \"Build a plugin that matches the repo's connector style\"\n\n## Guardrails\n\n- do not invent a new integration architecture when the repo already has one\n- do not start from vendor docs alone; start from existing in-repo connectors first\n- do not stop at transport code if the repo expects registry wiring, tests, and docs\n- do not cargo-cult old connectors if the repo has a newer current pattern\n\n## Workflow\n\n### 1. Learn the house style\n\nInspect at least 2 existing connectors\u002Fproviders and map:\n\n- file layout\n- abstraction boundaries\n- config model\n- retry \u002F pagination conventions\n- registry hooks\n- test fixtures and naming\n\n### 2. Narrow the target integration\n\nDefine only the surface the repo actually needs:\n\n- auth flow\n- key entities\n- core read\u002Fwrite operations\n- pagination and rate limits\n- webhook or polling model\n\n### 3. Build in repo-native layers\n\nTypical slices:\n\n- config\u002Fschema\n- client\u002Ftransport\n- mapping layer\n- connector\u002Fprovider entrypoint\n- registration\n- tests\n\n### 4. Validate against the source pattern\n\nThe new connector should look obvious in the codebase, not imported from a different ecosystem.\n\n## Reference Shapes\n\n### Provider-style\n\n```text\nproviders\u002F\n  existing_provider\u002F\n    __init__.py\n    provider.py\n    config.py\n```\n\n### Connector-style\n\n```text\nintegrations\u002F\n  existing\u002F\n    client.py\n    models.py\n    connector.py\n```\n\n### TypeScript plugin-style\n\n```text\nsrc\u002Fintegrations\u002F\n  existing\u002F\n    index.ts\n    client.ts\n    types.ts\n    test.ts\n```\n\n## Quality Checklist\n\n- [ ] matches an existing in-repo integration pattern\n- [ ] config validation exists\n- [ ] auth and error handling are explicit\n- [ ] pagination\u002Fretry behavior follows repo norms\n- [ ] registry\u002Fdiscovery wiring is complete\n- [ ] tests mirror the host repo's style\n- [ ] docs\u002Fexamples are updated if expected by the repo\n\n## Related Skills\n\n- `backend-patterns`\n- `mcp-server-patterns`\n- `github-ops`\n",{"name":5,"origin":24,"version":25,"description":7},"ECC direct-port adaptation","1.0.0","main","481dcd7dd2e288b9d627a2bd017db70e64e6c6fa",".claude\u002Fskills\u002Fapi-connector-builder",2,"https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI","https:\u002F\u002Fyana.vutam.link\u002F","https:\u002F\u002Fgithub.com\u002FHoronomos-laps","https:\u002F\u002Fyana.vutam.link","An open-source governed runtime & execution environment for multi-agent AI systems.","2026-11-14 13:24:09",{"source":8,"skillName":5,"commands":37,"prompt":47,"zipAvailable":48},[38,41,44],{"tool":39,"command":40},"npx","npx skills add Horonomos-laps\u002FYana-AI --skill api-connector-builder",{"tool":42,"command":43},"bunx","bunx skills add Horonomos-laps\u002FYana-AI --skill api-connector-builder",{"tool":45,"command":46},"pnpm","pnpm dlx skills add Horonomos-laps\u002FYana-AI --skill api-connector-builder","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fapi-connector-builder\u002FSKILL.md",true,[],[51,59,66,74,82,90],{"skillNo":52,"name":53,"nameZh":6,"description":54,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":55,"licenseFileUrl":6,"sourceHtmlUrl":56,"categories":57,"keywords":58,"publishedAt":19},"01M735GKET5YVYKAY62W2P5YXB","openai--sentry--sentry","Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.","MIT","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fopenai--sentry--sentry\u002FSKILL.md",[],[],{"skillNo":60,"name":61,"nameZh":6,"description":62,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":63,"categories":64,"keywords":65,"publishedAt":19},"01M73DCAP83T17HY7SMGK7MGFE","ito-basket-compare","Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fito-basket-compare\u002FSKILL.md",[],[],{"skillNo":67,"name":68,"nameZh":6,"description":69,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":70,"sourceHtmlUrl":71,"categories":72,"keywords":73,"publishedAt":19},"01M734CYEMZFDR3KH6SW0JP8TD","implementing-network-traffic-baselining","Build network traffic baselines from NetFlow\u002FIPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly\u002Fdaily traffic pattern profiling","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-network-traffic-baselining\u002FSKILL.md",[],[],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":78,"sourceHtmlUrl":79,"categories":80,"keywords":81,"publishedAt":19},"01M73ASZ6NJRJM44Z2P84NGQ3Q","detecting-evasion-techniques-in-endpoint-logs","Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002Fcore\u002Fskills\u002Fdetecting-evasion-techniques-in-endpoint-logs\u002FSKILL.md",[],[],{"skillNo":83,"name":84,"nameZh":6,"description":85,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":86,"sourceHtmlUrl":87,"categories":88,"keywords":89,"publishedAt":19},"01M734AFNXD06Z78QRK0VKGT7Q","implementing-microsegmentation-with-guardicore","Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.","https:\u002F\u002Fgithub.com\u002Fyanacuti1121\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Fimplementing-microsegmentation-with-guardicore\u002FSKILL.md",[],[],{"skillNo":91,"name":92,"nameZh":6,"description":6,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":93,"categories":94,"keywords":95,"publishedAt":19},"01M736TK27QMCXK0DVCH25SJN5","ramdisk-tmpfs-patterns","https:\u002F\u002Fgithub.com\u002FHoronomos-laps\u002FYana-AI\u002Fblob\u002Fmain\u002F.claude\u002Fskills\u002Framdisk-tmpfs-patterns\u002FSKILL.md",[],[]]