Initial commit: workspace setup with skills, memory, config
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skills/qdrant-memory/SKILL.md
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skills/qdrant-memory/SKILL.md
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---
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name: qdrant-memory
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description: |
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Manual memory backup to Qdrant vector database.
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Memories are stored ONLY when explicitly requested by the user.
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No automatic storage, no proactive retrieval, no background consolidation.
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Enhanced metadata (confidence, source, expiration) available for manual use.
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Includes separate KB collection for documents, web data, etc.
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metadata:
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openclaw:
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os: ["darwin", "linux", "win32"]
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---
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# Qdrant Memory - Manual Mode
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## Overview
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**MODE: MANUAL ONLY**
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This system provides manual memory storage to Qdrant vector database for semantic search.
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- **File-based logs**: Daily notes (`memory/YYYY-MM-DD.md`) continue normally
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- **Vector storage**: Qdrant available ONLY when user explicitly requests storage
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- **No automatic operations**: No auto-storage, no proactive retrieval, no auto-consolidation
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## Collections
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### `kimi_memories` (Personal Memories)
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- **Purpose**: Personal memories, preferences, rules, lessons learned
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- **Vector size**: 1024 (snowflake-arctic-embed2)
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- **Distance**: Cosine
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- **Usage**: "q remember", "q save", "q recall"
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### `kimi_kb` (Knowledge Base)
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- **Purpose**: Web search results, documents, scraped data, reference materials
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- **Vector size**: 1024 (snowflake-arctic-embed2)
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- **Distance**: Cosine
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- **Usage**: Manual storage of external data only when requested
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## Architecture
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### Storage Layers
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```
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Session Memory (this conversation) - Normal operation
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↓
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Daily Logs (memory/YYYY-MM-DD.md) - Automatic, file-based
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↓
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Manual Qdrant Storage - ONLY when user says "store this" or "q [command]"
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↓
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├── kimi_memories (personal) - "q remember", "q recall"
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└── kimi_kb (knowledge base) - web data, docs, manual only
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```
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### Memory Metadata
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Available when manually storing:
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- **text**: The memory content
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- **date**: Creation date
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- **tags**: Topics/keywords
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- **importance**: low/medium/high
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- **confidence**: high/medium/low (accuracy of the memory)
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- **source_type**: user/inferred/external (how it was obtained)
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- **verified**: bool (has this been confirmed)
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- **expires_at**: Optional expiration date
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- **related_memories**: IDs of connected memories
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- **access_count**: How many times retrieved
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- **last_accessed**: When last retrieved
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## Scripts
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### For kimi_memories (Personal)
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#### store_memory.py
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**Manual storage only** - Store with full metadata support:
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```bash
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# Basic manual storage
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python3 store_memory.py "Memory text" --importance high
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# With full metadata
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python3 store_memory.py "Memory text" \
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--importance high \
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--confidence high \
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--source-type user \
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--verified \
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--tags "preference,voice" \
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--expires 2026-03-01 \
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--related id1,id2
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```
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#### search_memories.py
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Manual search of stored memories:
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```bash
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# Basic search
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python3 search_memories.py "voice setup"
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# Filter by tag
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python3 search_memories.py "voice" --filter-tag "preference"
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# JSON output
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python3 search_memories.py "query" --json
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```
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### For kimi_kb (Knowledge Base)
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#### kb_store.py
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Store external data to KB:
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```bash
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# Store web page content
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python3 kb_store.py "Content text" \
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--title "Page Title" \
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--url "https://example.com" \
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--domain "Tech" \
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--tags "docker,containerization"
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# Store document excerpt
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python3 kb_store.py "Document content" \
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--title "API Documentation" \
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--source "docs.openclaw.ai" \
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--domain "OpenClaw" \
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--tags "api,reference"
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```
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#### kb_search.py
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Search knowledge base:
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```bash
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# Basic search
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python3 kb_search.py "docker volumes"
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# Filter by domain
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python3 kb_search.py "query" --domain "OpenClaw"
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# Include source URLs
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python3 kb_search.py "query" --include-urls
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```
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### Hybrid Search (Both Collections)
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#### hybrid_search.py
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Search both files and vectors (manual use):
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```bash
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python3 hybrid_search.py "query" --file-limit 3 --vector-limit 3
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```
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## Usage Rules
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### When to Store to Qdrant
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**ONLY** when user explicitly requests:
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- "Remember this..." → kimi_memories
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- "Store this in Qdrant..." → kimi_memories
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- "q save..." → kimi_memories
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- "Add to KB..." → kimi_kb
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- "Store this document..." → kimi_kb
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### What NOT to Do
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❌ **DO NOT** automatically store any memories to either collection
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❌ **DO NOT** auto-scrape web data to kimi_kb
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❌ **DO NOT** run proactive retrieval
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❌ **DO NOT** auto-consolidate
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## Manual Integration
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### Personal Memories (kimi_memories)
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```bash
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# Only when user explicitly says "q remember"
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python3 store_memory.py "User prefers X" --importance high --tags "preference"
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# Only when user explicitly says "q recall"
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python3 search_memories.py "query"
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```
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### Knowledge Base (kimi_kb)
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```bash
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# Only when user explicitly requests KB storage
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python3 kb_store.py "Content" --title "X" --domain "Y" --tags "z"
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# Search KB only when requested
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python3 kb_search.py "query"
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```
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## Best Practices
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1. **Wait for explicit request** - Never auto-store to either collection
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2. **Use right collection**:
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- Personal/lessons → `kimi_memories`
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- Documents/web data → `kimi_kb`
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3. **Always tag memories** - Makes retrieval more accurate
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4. **Include source for KB** - URL, document name, etc.
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5. **File-based memory continues normally** - Daily logs still automatic
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## Troubleshooting
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**Q: Qdrant not storing?**
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- Check Qdrant is running: `curl http://10.0.0.40:6333/`
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- Verify user explicitly requested storage
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**Q: Search returning wrong results?**
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- Try hybrid search for better recall
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- Use `--filter-tag` for precision
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---
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**CONFIGURATION: Manual Mode Only**
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**Collections: kimi_memories (personal), kimi_kb (knowledge base)**
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**Last Updated: 2026-02-10**
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