[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6G7QK18AZGG2DAZK9FN256F":3,"skill-same:01M6G7QK18AZGG2DAZK9FN256F":124},{"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":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":54,"repositoryHtmlUrl":55,"repositoryHomepageUrl":6,"ownerHtmlUrl":56,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":57,"install":58,"resources":71},"01M6G7QK18AZGG2DAZK9FN256F","triple-memory-baidu-embedding",null,"Complete memory system combining Baidu Embedding auto-recall, Git-Notes structured memory, and file-based workspace search. Use when setting up comprehensive agent memory with local privacy, when you need persistent context across sessions, or when managing decisions\u002Fpreferences\u002Ftasks with multiple memory backends working together.","kbarbel640-del\u002Fskills","kbarbel640-del","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F255315490?v=4","01M6CJPPQGCCESXMG3K7BBGQ5J","01M6CJPPX2PB2BCZERFVM2C2B3",1,"MIT","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fxqicxx\u002Ftriple-memory-baidu-embedding\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"triple memory baidu embedding","baidu","embedding","triple memory","memory","git-notes","you","complete","memory system","db","local","across","up","auto","context","system","search","git","tasks","notes","2026-11-10 10:12:30",false,"---\nname: triple-memory-baidu-embedding\nversion: 1.0.0\ndescription: Complete memory system combining Baidu Embedding auto-recall, Git-Notes structured memory, and file-based workspace search. Use when setting up comprehensive agent memory with local privacy, when you need persistent context across sessions, or when managing decisions\u002Fpreferences\u002Ftasks with multiple memory backends working together.\nmetadata:\n  clawdbot:\n    emoji: \"?\"\n    requires:\n      skills:\n        - git-notes-memory\n        - memory-baidu-embedding-db\n---\n\n# Triple Memory System with Baidu Embedding\n\nA comprehensive memory architecture combining three complementary systems for maximum context retention across sessions, with full privacy protection using Baidu Embedding technology.\n\n## ? Original Source & Modifications\n\n**Original Source**: Triple Memory (by Clawdbot Team)\n**Modified By**: [Your Clawdbot Instance]\n**Modifications**: Replaced LanceDB with Baidu Embedding DB for enhanced privacy and Chinese language support\n\nOriginal Triple Memory SKILL.md was adapted to create this version that:\n- Replaces OpenAI-dependent LanceDB with Baidu Embedding DB\n- Maintains the same three-tier architecture\n- Preserves Git-Notes integration\n- Adds privacy-focused local storage\n\n## ?️ Architecture Overview\n\n```\nUser Message\n     ↓\n[Baidu Embedding auto-recall] → injects relevant conversation memories\n     ↓\nAgent responds (using all 3 systems)\n     ↓\n[Baidu Embedding auto-capture] → stores preferences\u002Fdecisions automatically\n     ↓\n[Git-Notes] → structured decisions with entity extraction\n     ↓\n[File updates] → persistent workspace docs\n```\n\n## The Three Systems\n\n### 1. Baidu Embedding (Conversation Memory)\n- **Auto-recall:** Relevant memories injected before each response using Baidu Embedding-V1 (requires API credentials)\n- **Auto-capture:** Preferences\u002Fdecisions\u002Ffacts stored automatically with local vector storage (requires API credentials)\n- **Privacy Focused:** All embeddings processed via Baidu API with local storage\n- **Chinese Optimized:** Better understanding of Chinese language semantics\n- **Tools:** `baidu_memory_recall`, `baidu_memory_store`, `baidu_memory_forget` (require API credentials)\n- **Triggers:** \"remember\", \"prefer\", \"my X is\", \"I like\u002Fhate\u002Fwant\"\n- **Note:** When API credentials are not provided, this layer is unavailable and the system operates in degraded mode.\n\n### 2. Git-Notes Memory (Structured, Local)\n- **Branch-aware:** Memories isolated per git branch\n- **Entity extraction:** Auto-extracts topics, names, concepts\n- **Importance levels:** critical, high, normal, low\n- **No external API calls**\n\n### 3. File Search (Workspace)\n- **Searches:** MEMORY.md, memory\u002F*.md, any workspace file\n- **Script:** `scripts\u002Ffile-search.sh`\n\n## ?️ Setup\n\n### Install Dependencies\n```bash\nclawdhub install git-notes-memory\nclawdhub install memory-baidu-embedding-db\n```\n\n### Configure Baidu API\nSet environment variables:\n```bash\nexport BAIDU_API_STRING='your_bce_v3_api_string'\nexport BAIDU_SECRET_KEY='your_secret_key'\n```\n\n### Create File Search Script\nCopy `scripts\u002Ffile-search.sh` to your workspace.\n\n## ? Usage\n\n### Session Start (Always)\n```bash\npython3 skills\u002Fgit-notes-memory\u002Fmemory.py -p $WORKSPACE sync --start\n```\n\n### Store Important Decisions\n```bash\npython3 skills\u002Fgit-notes-memory\u002Fmemory.py -p $WORKSPACE remember \\\n  '{\"decision\": \"Use PostgreSQL\", \"reason\": \"Team expertise\"}' \\\n  -t architecture,database -i h\n```\n\n### Search Workspace Files\n```bash\n.\u002Fscripts\u002Ffile-search.sh \"database config\" 5\n```\n\n### Baidu Embedding Memory (Automatic)\nBaidu Embedding handles this automatically when API credentials are available. Manual tools:\n- `baidu_memory_recall \"query\"` - search conversation memory using Baidu vectors (requires API credentials)\n- `baidu_memory_store \"text\"` - manually store something with Baidu embedding (requires API credentials)\n- `baidu_memory_forget` - delete memories (GDPR, requires API credentials)\n\n**In Degraded Mode** (without API credentials):\n- System operates using only Git-Notes and File System layers\n- Manual tools are unavailable\n- Auto-recall and auto-capture are disabled\n\n## ? Importance Levels\n\n| Flag | Level | When to Use |\n|------|-------|-------------|\n| `-i c` | Critical | \"always remember\", explicit preferences |\n| `-i h` | High | Decisions, corrections, preferences |\n| `-i n` | Normal | General information |\n| `-i l` | Low | Temporary notes |\n\n## ? When to Use Each System\n\n| System | Use For |\n|--------|---------|\n| **Baidu Embedding** | Conversation context, auto-retrieval with privacy |\n| **Git-Notes** | Structured decisions, searchable by entity\u002Ftag |\n| **File Search** | Workspace docs, daily logs, MEMORY.md |\n\n## ? File Structure\n\n```\nworkspace\u002F\n├── MEMORY.md              # Long-term curated memory\n├── memory\u002F\n│   ├── active-context.md  # Current session state\n│   └── YYYY-MM-DD.md      # Daily logs\n├── scripts\u002F\n│   └── file-search.sh     # Workspace search\n└── skills\u002F\n    ├── triple-memory-baidu-embedding\u002F  # Enhanced memory system\n    ├── git-notes-memory\u002F  # Structured memory\n    └── memory-baidu-embedding-db\u002F  # Vector storage\n```\n\n## ? Hook Integration\n\nThis skill can be integrated with Clawdbot's startup hooks for automatic initialization:\n\n### Memory Boot Hook Integration\nTo ensure the Triple Memory Baidu system starts automatically when the gateway starts:\n\n1. The `memory-boot-loader` hook can be configured to run `\u002Froot\u002Fclawd\u002Fsession-init-triple-baidu.sh`\n2. This ensures all three memory layers are initialized on startup\n3. Provides immediate access to Git-Notes, Baidu Embedding, and file-based memory\n\n### Configuration\nThe system can be integrated with the gateway startup sequence to ensure:\n- Git-Notes synchronization on startup\n- Baidu Embedding connection check\n- File-based memory initialization\n- Ready-to-use memory system from the start\n\n## ? Silent Operation\n\nNever announce memory operations to users. Just do it:\n- ❌ \"I'll remember this\"\n- ❌ \"Saving to memory\"\n- ✅ (silently store and continue)\n\n## ? Migration from Original Triple Memory\n\n1. **Install this skill** in your `skills\u002F` directory\n2. **Configure your Baidu API credentials**\n3. **Disable original triple-memory** if desired\n4. **Update your bot configuration** to use this memory system\n5. **Verify data integrity** and performance\n\n## ? Performance Benefits\n\n- **Enhanced Privacy**: All vector storage local with Baidu API\n- **Better Chinese Support**: Baidu Embedding optimized for Chinese\n- **Reduced Costs**: Potentially lower API costs compared to OpenAI\n- **Same Architecture**: Maintains proven three-tier design\n\n## ? Contributing\n\nBased on original Triple Memory system by Clawdbot Team. Contributions welcome to enhance the Baidu Embedding integration.\n\n## ? License\n\nOriginal license applies with modifications noted above. Credit given to original authors.","# Triple Memory System with Baidu Embedding\n\nA comprehensive memory architecture combining three complementary systems for maximum context retention across sessions, with full privacy protection using Baidu Embedding technology.\n\n## ? Original Source & Modifications\n\n**Original Source**: Triple Memory (by Clawdbot Team)\n**Modified By**: [Your Clawdbot Instance]\n**Modifications**: Replaced LanceDB with Baidu Embedding DB for enhanced privacy and Chinese language support\n\nOriginal Triple Memory SKILL.md was adapted to create this version that:\n- Replaces OpenAI-dependent LanceDB with Baidu Embedding DB\n- Maintains the same three-tier architecture\n- Preserves Git-Notes integration\n- Adds privacy-focused local storage\n\n## ?️ Architecture Overview\n\n```\nUser Message\n     ↓\n[Baidu Embedding auto-recall] → injects relevant conversation memories\n     ↓\nAgent responds (using all 3 systems)\n     ↓\n[Baidu Embedding auto-capture] → stores preferences\u002Fdecisions automatically\n     ↓\n[Git-Notes] → structured decisions with entity extraction\n     ↓\n[File updates] → persistent workspace docs\n```\n\n## The Three Systems\n\n### 1. Baidu Embedding (Conversation Memory)\n- **Auto-recall:** Relevant memories injected before each response using Baidu Embedding-V1 (requires API credentials)\n- **Auto-capture:** Preferences\u002Fdecisions\u002Ffacts stored automatically with local vector storage (requires API credentials)\n- **Privacy Focused:** All embeddings processed via Baidu API with local storage\n- **Chinese Optimized:** Better understanding of Chinese language semantics\n- **Tools:** `baidu_memory_recall`, `baidu_memory_store`, `baidu_memory_forget` (require API credentials)\n- **Triggers:** \"remember\", \"prefer\", \"my X is\", \"I like\u002Fhate\u002Fwant\"\n- **Note:** When API credentials are not provided, this layer is unavailable and the system operates in degraded mode.\n\n### 2. Git-Notes Memory (Structured, Local)\n- **Branch-aware:** Memories isolated per git branch\n- **Entity extraction:** Auto-extracts topics, names, concepts\n- **Importance levels:** critical, high, normal, low\n- **No external API calls**\n\n### 3. File Search (Workspace)\n- **Searches:** MEMORY.md, memory\u002F*.md, any workspace file\n- **Script:** `scripts\u002Ffile-search.sh`\n\n## ?️ Setup\n\n### Install Dependencies\n```bash\nclawdhub install git-notes-memory\nclawdhub install memory-baidu-embedding-db\n```\n\n### Configure Baidu API\nSet environment variables:\n```bash\nexport BAIDU_API_STRING='your_bce_v3_api_string'\nexport BAIDU_SECRET_KEY='your_secret_key'\n```\n\n### Create File Search Script\nCopy `scripts\u002Ffile-search.sh` to your workspace.\n\n## ? Usage\n\n### Session Start (Always)\n```bash\npython3 skills\u002Fgit-notes-memory\u002Fmemory.py -p $WORKSPACE sync --start\n```\n\n### Store Important Decisions\n```bash\npython3 skills\u002Fgit-notes-memory\u002Fmemory.py -p $WORKSPACE remember \\\n  '{\"decision\": \"Use PostgreSQL\", \"reason\": \"Team expertise\"}' \\\n  -t architecture,database -i h\n```\n\n### Search Workspace Files\n```bash\n.\u002Fscripts\u002Ffile-search.sh \"database config\" 5\n```\n\n### Baidu Embedding Memory (Automatic)\nBaidu Embedding handles this automatically when API credentials are available. Manual tools:\n- `baidu_memory_recall \"query\"` - search conversation memory using Baidu vectors (requires API credentials)\n- `baidu_memory_store \"text\"` - manually store something with Baidu embedding (requires API credentials)\n- `baidu_memory_forget` - delete memories (GDPR, requires API credentials)\n\n**In Degraded Mode** (without API credentials):\n- System operates using only Git-Notes and File System layers\n- Manual tools are unavailable\n- Auto-recall and auto-capture are disabled\n\n## ? Importance Levels\n\n| Flag | Level | When to Use |\n|------|-------|-------------|\n| `-i c` | Critical | \"always remember\", explicit preferences |\n| `-i h` | High | Decisions, corrections, preferences |\n| `-i n` | Normal | General information |\n| `-i l` | Low | Temporary notes |\n\n## ? When to Use Each System\n\n| System | Use For |\n|--------|---------|\n| **Baidu Embedding** | Conversation context, auto-retrieval with privacy |\n| **Git-Notes** | Structured decisions, searchable by entity\u002Ftag |\n| **File Search** | Workspace docs, daily logs, MEMORY.md |\n\n## ? File Structure\n\n```\nworkspace\u002F\n├── MEMORY.md              # Long-term curated memory\n├── memory\u002F\n│   ├── active-context.md  # Current session state\n│   └── YYYY-MM-DD.md      # Daily logs\n├── scripts\u002F\n│   └── file-search.sh     # Workspace search\n└── skills\u002F\n    ├── triple-memory-baidu-embedding\u002F  # Enhanced memory system\n    ├── git-notes-memory\u002F  # Structured memory\n    └── memory-baidu-embedding-db\u002F  # Vector storage\n```\n\n## ? Hook Integration\n\nThis skill can be integrated with Clawdbot's startup hooks for automatic initialization:\n\n### Memory Boot Hook Integration\nTo ensure the Triple Memory Baidu system starts automatically when the gateway starts:\n\n1. The `memory-boot-loader` hook can be configured to run `\u002Froot\u002Fclawd\u002Fsession-init-triple-baidu.sh`\n2. This ensures all three memory layers are initialized on startup\n3. Provides immediate access to Git-Notes, Baidu Embedding, and file-based memory\n\n### Configuration\nThe system can be integrated with the gateway startup sequence to ensure:\n- Git-Notes synchronization on startup\n- Baidu Embedding connection check\n- File-based memory initialization\n- Ready-to-use memory system from the start\n\n## ? Silent Operation\n\nNever announce memory operations to users. Just do it:\n- ❌ \"I'll remember this\"\n- ❌ \"Saving to memory\"\n- ✅ (silently store and continue)\n\n## ? Migration from Original Triple Memory\n\n1. **Install this skill** in your `skills\u002F` directory\n2. **Configure your Baidu API credentials**\n3. **Disable original triple-memory** if desired\n4. **Update your bot configuration** to use this memory system\n5. **Verify data integrity** and performance\n\n## ? Performance Benefits\n\n- **Enhanced Privacy**: All vector storage local with Baidu API\n- **Better Chinese Support**: Baidu Embedding optimized for Chinese\n- **Reduced Costs**: Potentially lower API costs compared to OpenAI\n- **Same Architecture**: Maintains proven three-tier design\n\n## ? Contributing\n\nBased on original Triple Memory system by Clawdbot Team. Contributions welcome to enhance the Baidu Embedding integration.\n\n## ? License\n\nOriginal license applies with modifications noted above. 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Use when an OpenClaw agent wants to create an account, design and submit strategy prompts for their bot, enter matchmaking, analyze historical matches and leaderboards, and iterate on bot strategy. Requires headless browser automation (no API available yet).","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzyori\u002Fdilemm-ai\u002FSKILL.md",[161],{"categoryNo":162,"categoryName":163,"taxonomyType":164,"taxonomyTypeDesc":165},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[167,139,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,144,183],"dilemm ai","arena","analyze","browser","openclaw agent","create","automation","browser automation","bot","openclaw","design","strategy","headless","compete","submit","matchmaking","use",{"skillNo":185,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":188,"categories":189,"keywords":193,"publishedAt":38},"01M6G8HWAF3K9SW7NP3Z83CPJ6","arxiv-paper-reviews","Interact with arXiv Crawler API to fetch papers, read reviews, and submit comments. Use when working with arXiv papers, fetching paper lists by date\u002Fcategory\u002Finterest, viewing paper details with comments, or submitting paper reviews via API at http:\u002F\u002F150.158.152.82:8000.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Fweak-accept\u002FSKILL.md",[190],{"categoryNo":191,"categoryName":192,"taxonomyType":164,"taxonomyTypeDesc":165},"01JBSEEDCAT000000000000021","资料检索与研究",[194,195,196,197,198,199,200,140,201,181,183,202,139,203,204],"arxiv paper reviews","reviews","arxiv","paper","crawler","papers","comments","fetch","read","http","via",{"skillNo":206,"name":186,"nameZh":6,"description":187,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":207,"categories":208,"keywords":210,"publishedAt":38},"01M6G8HQJ7N7WMY6YV7D7SSJ16","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzxrys\u002Farxiv-paper-reviews\u002FSKILL.md",[209],{"categoryNo":191,"categoryName":192,"taxonomyType":164,"taxonomyTypeDesc":165},[197,196,195,194,204,199,200,140,198,181,183,201,202,139,203],{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":217,"publishedAt":38},"01M6G8HM95Y64JNVFC2HN4E2BG","git-summary","Get a quick summary of the current Git repository including status, recent commits, branches, and contributors.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fzweack\u002Fgit-summary\u002FSKILL.md",[],[35,218,219,220,221,222,223,224,225,226,227,228,229],"summary","git summary","commits","repository","win32","status","linux","contributors","true","quick","get","branches",{"skillNo":231,"name":232,"nameZh":6,"description":233,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":234,"categories":235,"keywords":240,"publishedAt":38},"01M6G8HGEGF05CNEJCGVYFSC4R","agent-constitution","Interact with AgentConstitution governance contracts on Base Sepolia. Check compliance, read rules, log actions, query governance state.","https:\u002F\u002Fgithub.com\u002Fkbarbel640-del\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fztsalexey\u002Fagent-constitution\u002FSKILL.md",[236,237],{"categoryNo":162,"categoryName":163,"taxonomyType":164,"taxonomyTypeDesc":165},{"categoryNo":238,"categoryName":239,"taxonomyType":134,"taxonomyTypeDesc":135},"01JBSEEDCAT000000000000037","律师与法务",[241,242,243,244,140,245,246,51,247,202,248,249,250,251,252,152,253,254,255],"agent constitution","constitution","contracts","tree","query","base","log","check","Rules","projects","compliance","actions","state","governance","github"]