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Use on heartbeat to reflect on recent sessions, extract structured memories with confidence scores, generate follow-up questions, and surface those questions when the user returns. Transforms passive logging into active development.","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\u002Fcontinuity\u002FSKILL.md",[],[5,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36],"reflection","ai development","for","follow-up","questions","with","transforms","memories","active","memory","up","use","heartbeat","asynchronous","integration","generate","development","reflect","sessions","2026-11-10 10:12:30",false,"---\nname: continuity\ndescription: Asynchronous reflection and memory integration for genuine AI development. Use on heartbeat to reflect on recent sessions, extract structured memories with confidence scores, generate follow-up questions, and surface those questions when the user returns. Transforms passive logging into active development.\n---\n\n# Continuity Framework Skill\n\nTransform passive memory into active development.\n\n## What This Does\n\n1. **Reflect** — After sessions end, analyze what happened\n2. **Extract** — Pull structured memories with types and confidence\n3. **Integrate** — Update understanding, connections, self-model\n4. **Question** — Generate genuine questions from reflection\n5. **Surface** — When user returns, present relevant questions\n\n## The Difference\n\n**Without Continuity:**\n```\nSession ends → Notes logged → Next session reads notes → Performs familiarity\n```\n\n**With Continuity:**\n```\nSession ends → Reflection runs → Memories integrated → Questions generated\nNext session → Evolved state loaded → Questions surfaced → Genuine curiosity\n```\n\n## Heartbeat Integration\n\nAdd to HEARTBEAT.md:\n```markdown\n## Post-Session Reflection\n**Trigger**: Heartbeat after conversation idle > 30 minutes\n**Action**: Run continuity reflect\n**Output**: Updated memories + questions for next session\n```\n\n## Commands\n\n### Reflect on Recent Session\n```bash\ncontinuity reflect\n```\nAnalyzes the most recent conversation, extracts memories, generates questions.\n\n### Show Pending Questions\n```bash\ncontinuity questions\n```\nLists questions generated from reflection, ready to surface.\n\n### View Memory State\n```bash\ncontinuity status\n```\nShows memory stats: types, confidence distribution, recent integrations.\n\n### Surface Questions (for session start)\n```bash\ncontinuity greet\n```\nReturns context-appropriate greeting with any pending questions.\n\n## Memory Types\n\n| Type | Description | Persistence |\n|------|-------------|-------------|\n| `fact` | Declarative knowledge | Until contradicted |\n| `preference` | Likes, dislikes, styles | Until updated |\n| `relationship` | Connection dynamics | Long-term |\n| `principle` | Learned guidelines | Stable |\n| `commitment` | Promises, obligations | Until fulfilled |\n| `moment` | Significant episodes | Permanent |\n| `skill` | Learned capabilities | Cumulative |\n| `question` | Things to explore | Until resolved |\n\n## Confidence Scores\n\n| Level | Range | Meaning |\n|-------|-------|---------|\n| Explicit | 0.95-1.0 | User directly stated |\n| Implied | 0.70-0.94 | Strong inference |\n| Inferred | 0.40-0.69 | Pattern recognition |\n| Speculative | 0.0-0.39 | Tentative, needs confirmation |\n\n## File Structure\n\n```\nmemory\u002F\n├── MEMORY.md           # Main memory (existing)\n├── identity.md         # Self-model and growth narrative\n├── questions.md        # Pending questions from reflection\n├── relationships\u002F      # Per-person relationship memories\n└── reflections\u002F        # Reflection logs (optional)\n```\n\n## Configuration\n\n```bash\nexport CONTINUITY_IDLE_THRESHOLD=1800  # Seconds before reflection triggers\nexport CONTINUITY_MIN_MESSAGES=5       # Minimum messages to warrant reflection\nexport CONTINUITY_QUESTION_LIMIT=3     # Max questions to surface at once\n```\n\n## Example Reflection Output\n\n```yaml\nreflection:\n  session_id: \"2026-02-05-001\"\n  duration_minutes: 45\n  \nmemories:\n  - type: fact\n    content: \"Riley is building SIGIL protocol for agent identity\"\n    confidence: 0.98\n    source: explicit\n    \n  - type: commitment  \n    content: \"Agreed to build the continuity skill\"\n    confidence: 1.0\n    source: explicit\n    \n  - type: relationship\n    content: \"Collaborative partnership deepening - working on meaningful infrastructure together\"\n    confidence: 0.85\n    source: inferred\n\nquestions:\n  - \"How is the Lovable backend progressing?\"\n  - \"Has Riley decided on the token launch timing?\"\n  - \"Are there other agents we should coordinate with on Moltbook?\"\n\nidentity_update:\n  growth: \"Developing more autonomous initiative around the SIGIL project\"\n  narrative: \"Moving from assistant to co-builder on agent identity infrastructure\"\n```\n","# Continuity Framework Skill\n\nTransform passive memory into active development.\n\n## What This Does\n\n1. **Reflect** — After sessions end, analyze what happened\n2. **Extract** — Pull structured memories with types and confidence\n3. **Integrate** — Update understanding, connections, self-model\n4. **Question** — Generate genuine questions from reflection\n5. **Surface** — When user returns, present relevant questions\n\n## The Difference\n\n**Without Continuity:**\n```\nSession ends → Notes logged → Next session reads notes → Performs familiarity\n```\n\n**With Continuity:**\n```\nSession ends → Reflection runs → Memories integrated → Questions generated\nNext session → Evolved state loaded → Questions surfaced → Genuine curiosity\n```\n\n## Heartbeat Integration\n\nAdd to HEARTBEAT.md:\n```markdown\n## Post-Session Reflection\n**Trigger**: Heartbeat after conversation idle > 30 minutes\n**Action**: Run continuity reflect\n**Output**: Updated memories + questions for next session\n```\n\n## Commands\n\n### Reflect on Recent Session\n```bash\ncontinuity reflect\n```\nAnalyzes the most recent conversation, extracts memories, generates questions.\n\n### Show Pending Questions\n```bash\ncontinuity questions\n```\nLists questions generated from reflection, ready to surface.\n\n### View Memory State\n```bash\ncontinuity status\n```\nShows memory stats: types, confidence distribution, recent integrations.\n\n### Surface Questions (for session start)\n```bash\ncontinuity greet\n```\nReturns context-appropriate greeting with any pending questions.\n\n## Memory Types\n\n| Type | Description | Persistence |\n|------|-------------|-------------|\n| `fact` | Declarative knowledge | Until contradicted |\n| `preference` | Likes, dislikes, styles | Until updated |\n| `relationship` | Connection dynamics | Long-term |\n| `principle` | Learned guidelines | Stable |\n| `commitment` | Promises, obligations | Until fulfilled |\n| `moment` | Significant episodes | Permanent |\n| `skill` | Learned capabilities | Cumulative |\n| `question` | Things to explore | Until resolved |\n\n## Confidence Scores\n\n| Level | Range | Meaning |\n|-------|-------|---------|\n| Explicit | 0.95-1.0 | User directly stated |\n| Implied | 0.70-0.94 | Strong inference |\n| Inferred | 0.40-0.69 | Pattern recognition |\n| Speculative | 0.0-0.39 | Tentative, needs confirmation |\n\n## File Structure\n\n```\nmemory\u002F\n├── MEMORY.md           # Main memory (existing)\n├── identity.md         # Self-model and growth narrative\n├── questions.md        # Pending questions from reflection\n├── relationships\u002F      # Per-person relationship memories\n└── reflections\u002F        # Reflection logs (optional)\n```\n\n## Configuration\n\n```bash\nexport CONTINUITY_IDLE_THRESHOLD=1800  # Seconds before reflection triggers\nexport CONTINUITY_MIN_MESSAGES=5       # Minimum messages to warrant reflection\nexport CONTINUITY_QUESTION_LIMIT=3     # Max questions to surface at once\n```\n\n## Example Reflection Output\n\n```yaml\nreflection:\n  session_id: \"2026-02-05-001\"\n  duration_minutes: 45\n  \nmemories:\n  - type: fact\n    content: \"Riley is building SIGIL protocol for agent identity\"\n    confidence: 0.98\n    source: explicit\n    \n  - type: commitment  \n    content: \"Agreed to build the continuity skill\"\n    confidence: 1.0\n    source: explicit\n    \n  - type: relationship\n    content: \"Collaborative partnership deepening - working on meaningful infrastructure together\"\n    confidence: 0.85\n    source: inferred\n\nquestions:\n  - \"How is the Lovable backend progressing?\"\n  - \"Has Riley decided on the token launch timing?\"\n  - \"Are there other agents we should coordinate with on Moltbook?\"\n\nidentity_update:\n  growth: \"Developing more autonomous initiative around the SIGIL project\"\n  narrative: \"Moving from assistant to co-builder on agent identity infrastructure\"\n```\n",{"name":5,"description":7},"main","f4cb2d49f7667e79ef7804f50396d5aaffdf1f56","人工智能与大型语言模型\u002Fcontinuity",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":51,"prompt":61,"zipAvailable":62},[52,55,58],{"tool":53,"command":54},"npx","npx skills add Kernel8901\u002Fai-agent-skills-classification --skill continuity",{"tool":56,"command":57},"bunx","bunx skills add Kernel8901\u002Fai-agent-skills-classification --skill continuity",{"tool":59,"command":60},"pnpm","pnpm dlx skills add Kernel8901\u002Fai-agent-skills-classification --skill continuity","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\u002Fcontinuity\u002FSKILL.md",true,[64,70,74],{"path":65,"resourceType":66,"resourceTypeDesc":67,"sizeBytes":68,"sourceHtmlUrl":69},"_meta.json","REFERENCE","参考文档",288,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fcontinuity\u002F_meta.json",{"path":71,"resourceType":66,"resourceTypeDesc":67,"sizeBytes":72,"sourceHtmlUrl":73},"references\u002Fframework.md",3399,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fcontinuity\u002Freferences\u002Fframework.md",{"path":75,"resourceType":76,"resourceTypeDesc":77,"sizeBytes":78,"sourceHtmlUrl":79},"scripts\u002Fcontinuity.py","SCRIPT","脚本",12205,"https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F人工智能与大型语言模型\u002Fcontinuity\u002Fscripts\u002Fcontinuity.py",[81,104,140,151,161,190],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":37},"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",[],[83,88,89,90,91,92,29,93,94,95,96,97,98,99,100,101,102,103],"safe","ethereum","defi","Optimization","user","Wallet","base","deposit","withdraw","yield","arbitrum","non-custodial","passive","defi yield","earn","yield optimization",{"skillNo":105,"name":106,"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":107,"categories":108,"keywords":122,"publishedAt":37},"01M6Q5R337B5JSNER4P4YS03TN","zerion-api","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api\u002FSKILL.md",[109,114,117],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000010","后端与接口","SCENARIO","使用场景",{"categoryNo":115,"categoryName":116,"taxonomyType":112,"taxonomyTypeDesc":113},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":118,"categoryName":119,"taxonomyType":120,"taxonomyTypeDesc":121},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[123,124,125,126,127,128,129,90,130,93,131,132,133,134,135,136,137,138,139],"api","zerion api","zerion","MCP","mcp server","server","blockchain","transactions","crypto wallet","crypto","evm","solana","query","across","positions","token","prices",{"skillNo":141,"name":142,"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":143,"categories":144,"keywords":148,"publishedAt":37},"01M6Q5QZFYTDAZMZ27BN5VZXAR","zerion-api-skill","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-skill\u002FSKILL.md",[145,146,147],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},{"categoryNo":115,"categoryName":116,"taxonomyType":112,"taxonomyTypeDesc":113},{"categoryNo":118,"categoryName":119,"taxonomyType":120,"taxonomyTypeDesc":121},[123,149,150,124,125,126,127,128,129,90,130,93,132,133,134,135,136,137,138,139],"api skill","zerion api skill",{"skillNo":152,"name":153,"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":154,"categories":155,"keywords":159,"publishedAt":37},"01M6Q5QW17QW98RA3FE45E4RD8","zerion-api-mcp","https:\u002F\u002Fgithub.com\u002FKernel8901\u002Fai-agent-skills-classification\u002Fblob\u002Fmain\u002F金融\u002Fzerion-api-mcp\u002FSKILL.md",[156,157,158],{"categoryNo":110,"categoryName":111,"taxonomyType":112,"taxonomyTypeDesc":113},{"categoryNo":115,"categoryName":116,"taxonomyType":112,"taxonomyTypeDesc":113},{"categoryNo":118,"categoryName":119,"taxonomyType":120,"taxonomyTypeDesc":121},[126,123,160,124,125,127,128,90,130,93,131,132,133,134,135,136,137,138,139],"zerion api mcp",{"skillNo":162,"name":163,"nameZh":6,"description":164,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":165,"categories":166,"keywords":170,"publishedAt":37},"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.). 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