[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6JBVB7TRQBKWKAWAWA4F5MY":3,"skill-same:01M6JBVB7TRQBKWKAWAWA4F5MY":59},{"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":31,"linkOnly":32,"markdownContent":33,"markdownBody":34,"frontMatter":35,"refName":37,"commitSha":38,"skillDirectory":39,"forksCount":40,"repositoryHtmlUrl":41,"repositoryHomepageUrl":42,"ownerHtmlUrl":43,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":44,"install":45,"resources":58},"01M6JBVB7TRQBKWKAWAWA4F5MY","cognitive-memory",null,"Implementation and troubleshooting of the Cognitive Memory (Cognify) system in Hermes Agent.","S3YED\u002Fappie-kit","S3YED","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F62743867?v=4","01M6JBKBRRVP6KMS0VWZ27T3R6","01M6JBKBX0KG30284PW1DBYJT1",14,"MIT","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fautonomous-ai-agents\u002Fcognitive-memory\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],"memory","cognitive memory","system","troubleshooting","hermes","hermes agent","implementation","cognify","2026-11-10 10:12:30",false,"---\nname: cognitive-memory\ndescription: Implementation and troubleshooting of the Cognitive Memory (Cognify) system in Hermes Agent.\nversion: 1.0.0\n---\n\n# Cognitive Memory (Cognify)\n\nThe Cognitive Memory system (PR #727, codenamed \"Cognify\") provides Hermes Agent with semantic recall, auto-encoding, contradiction detection, and exponential forgetting.\n\n## Architecture\n\n- `cognitive_memory\u002F`: Core logic (store, embeddings, recall, encoding, extraction).\n- `tools\u002Fcognitive_memory_tool.py`: Agent-facing `cognitive_recall` tool.\n- Database: `~\u002F.hermes\u002Fcognitive_memory.db` (SQLite).\n\n## Setup & Configuration\n\nEnable in `~\u002F.hermes\u002Fconfig.yaml`:\n\n```yaml\ncognitive_memory:\n  enabled: true\n  embedding:\n    model: \"text-embedding-3-small\"\n```\n\n## Known Issues & Workarounds\n\n### Dependency: litellm\nCognify depends on `litellm`. On macOS systems with Homebrew Python, you may encounter `pyexpat` errors related to `Symbol not found: _XML_SetAllocTrackerActivationThreshold`.\n\n**Fix:**\n```bash\nexport DYLD_LIBRARY_PATH=\u002Fopt\u002Fhomebrew\u002Fopt\u002Fexpat\u002Flib\npython3.13 -m pip install litellm --break-system-packages\n```\n\n### Manual Installation (from PR branch)\nIf the system is not yet merged, files must be extracted from the `cognitive-memory` branch:\n1. `git fetch origin pull\u002F727\u002Fhead:cognitive-memory`\n2. `git show cognitive-memory:path\u002Fto\u002Ffile > path\u002Fto\u002Ffile`\n3. Tools must be registered in `tools\u002Fregistry.py` (standard auto-discovery usually handles this if `cognitive_memory_tool.py` is in the `tools\u002F` dir).\n\n## Tool usage: cognitive_recall\n\n- `action='store', content='...'`: Saves to semantic memory.\n- `action='recall', query='...'`: Retrieves by meaning.\n- `action='forget', query='...'`: Deletes matching items.\n- `action='status'`: Shows database stats.\n","# Cognitive Memory (Cognify)\n\nThe Cognitive Memory system (PR #727, codenamed \"Cognify\") provides Hermes Agent with semantic recall, auto-encoding, contradiction detection, and exponential forgetting.\n\n## Architecture\n\n- `cognitive_memory\u002F`: Core logic (store, embeddings, recall, encoding, extraction).\n- `tools\u002Fcognitive_memory_tool.py`: Agent-facing `cognitive_recall` tool.\n- Database: `~\u002F.hermes\u002Fcognitive_memory.db` (SQLite).\n\n## Setup & Configuration\n\nEnable in `~\u002F.hermes\u002Fconfig.yaml`:\n\n```yaml\ncognitive_memory:\n  enabled: true\n  embedding:\n    model: \"text-embedding-3-small\"\n```\n\n## Known Issues & Workarounds\n\n### Dependency: litellm\nCognify depends on `litellm`. On macOS systems with Homebrew Python, you may encounter `pyexpat` errors related to `Symbol not found: _XML_SetAllocTrackerActivationThreshold`.\n\n**Fix:**\n```bash\nexport DYLD_LIBRARY_PATH=\u002Fopt\u002Fhomebrew\u002Fopt\u002Fexpat\u002Flib\npython3.13 -m pip install litellm --break-system-packages\n```\n\n### Manual Installation (from PR branch)\nIf the system is not yet merged, files must be extracted from the `cognitive-memory` branch:\n1. `git fetch origin pull\u002F727\u002Fhead:cognitive-memory`\n2. `git show cognitive-memory:path\u002Fto\u002Ffile > path\u002Fto\u002Ffile`\n3. Tools must be registered in `tools\u002Fregistry.py` (standard auto-discovery usually handles this if `cognitive_memory_tool.py` is in the `tools\u002F` dir).\n\n## Tool usage: cognitive_recall\n\n- `action='store', content='...'`: Saves to semantic memory.\n- `action='recall', query='...'`: Retrieves by meaning.\n- `action='forget', query='...'`: Deletes matching items.\n- `action='status'`: Shows database stats.\n",{"name":5,"version":36,"description":7},"1.0.0","master","8ec37df6d71fb664ea19d32c079e7d3ff931a8e0","skills\u002Fautonomous-ai-agents\u002Fcognitive-memory",3,"https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit","https:\u002F\u002Fweblyfe.ai","https:\u002F\u002Fgithub.com\u002FS3YED","2026-08-27 01:54:02",{"source":8,"skillName":5,"commands":46,"prompt":56,"zipAvailable":57},[47,50,53],{"tool":48,"command":49},"npx","npx skills add S3YED\u002Fappie-kit --skill cognitive-memory",{"tool":51,"command":52},"bunx","bunx skills add S3YED\u002Fappie-kit --skill cognitive-memory",{"tool":54,"command":55},"pnpm","pnpm dlx skills add S3YED\u002Fappie-kit --skill cognitive-memory","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fautonomous-ai-agents\u002Fcognitive-memory\u002FSKILL.md",true,[],[60,90,124,150,181,206],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":73,"publishedAt":31},"01M6JFD4M6N4DSGC7TXEJ5R3J2","ai-music","AI music generation and audio tools: HeartMuLa lyrics-to-music generation, songwriting craft (+ Suno prompts), and audio spectrogram\u002Ffeature visualization.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fwethlete\u002Fai-music\u002FSKILL.md",[66,69,72],{"categoryNo":67,"categoryName":68,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":70,"categoryName":71,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[74,75,76,77,78,79,27,28,80,81,82,83,84,85,86,87,88,89],"music","ai music","humanizer","visualization","Tools","Audio","songwriting","suno","lyrics","prompts","heartmula","craft","generation","feature","ai music generation","music generation",{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":104,"publishedAt":31},"01M6JFCZE4XNFQFMNZDHKHT5V5","agentic-webdesign-design-system-ingestion","Use v0 Design Systems 2.0, Bolt Design System Agents, or Lovable to generate production UI from a client's real design system components — not generic Tailwind. Use when building a client website where brand consistency matters.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-design-system-ingestion\u002FSKILL.md",[96,99],{"categoryNo":97,"categoryName":98,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":100,"categoryName":101,"taxonomyType":102,"taxonomyTypeDesc":103},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[105,106,107,25,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123],"design","agentic","design system","ingestion","webdesign","agentic webdesign design system ingestion","components","generate","design systems","website","ui","Tailwind","bolt","lovable","v0","design-system","wed","design system components","appie",{"skillNo":125,"name":126,"nameZh":6,"description":127,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":128,"categories":129,"keywords":132,"publishedAt":31},"01M6JFCVPX3913CFAS6QQJ33ZB","agentic-webdesign-agent-elements","Use 21st.dev Agent Elements — 25 shadcn\u002Fui components purpose-built for AI agent UIs. Tool cards (Bash, Edit, Search, Plan, Subagent, MCP), chat, input, streaming. Open source, shadcn-registry install, no runtime lock-in.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fweb-design\u002Fagentic-webdesign-agent-elements\u002FSKILL.md",[130,131],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},{"categoryNo":100,"categoryName":101,"taxonomyType":102,"taxonomyTypeDesc":103},[106,133,109,134,135,136,111,137,138,139,140,141,142,143,144,145,146,147,148,149],"elements","agentic webdesign agent elements","MCP","ai agent","registry","search","streaming","open source","open","Bash","plan","subagent","edit","install","input","lock","source",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":160,"publishedAt":31},"01M6JFCQC7H65M9QJ6TRE71BS1","vercel-deployment","Deploy static sites and frontends to Vercel — handles both CLI and REST API paths, including the CLI token sanitization workaround.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fvercel-deployment\u002FSKILL.md",[156,159],{"categoryNo":157,"categoryName":158,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180],"deployment","vercel deployment","vercel","macos","cli","linux","windows","deploy","vercel deploy","REST","api","site","deploy to vercel","token","rest api","host","sites","paths","sanitization","static site",{"skillNo":182,"name":183,"nameZh":6,"description":184,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":185,"categories":186,"keywords":188,"publishedAt":31},"01M6JFCM4SMTXBM5A01BK2YQG1","software-quality-workflows","Umbrella workflow for TDD, debugging, code simplification, spikes, pre-commit review, and debugger-assisted investigation.","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Fsoftware-quality-workflows\u002FSKILL.md",[187],{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[189,190,191,192,193,194,195,196,197,198,199,200,201,202,203,204,205],"workflows","quality","software","software quality workflows","review","tdd","workflow","commit","debugging","code","debugger","pre-commit","investigation","code simplification","user","simplification","for",{"skillNo":207,"name":208,"nameZh":6,"description":209,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":210,"categories":211,"keywords":219,"publishedAt":31},"01M6JFCGD0M6CEATY01W7YN6DB","react-component-refactoring","Safely refactor large React components into smaller, maintainable pieces using proven patterns","https:\u002F\u002Fgithub.com\u002FS3YED\u002Fappie-kit\u002Fblob\u002Fmaster\u002Fskills\u002Fsoftware-development\u002Freact-component-refactoring\u002FSKILL.md",[212,215,218],{"categoryNo":213,"categoryName":214,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000007","代码审查",{"categoryNo":216,"categoryName":217,"taxonomyType":20,"taxonomyTypeDesc":21},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":18,"categoryName":19,"taxonomyType":20,"taxonomyTypeDesc":21},[220,221,222,223,224,225,226,227,164,228,229,111,230,167,231,198,232,233,234,235],"react","component","refactoring","component refactoring","react component","react component refactoring","frontend","writing","safe","typescript","react components","modular","refactor","simplify","patterns","test-driven-development"]