Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Productivity
triple-memory-baidu-embedding
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/preferences/tasks with multiple memory backends working together.
skill openclawclawhub Free
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/preferences/tasks with multiple memory backends working together.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- CREDITS.md, install.sh, README.md, USAGE_EXAMPLES.md, SKILL.md, configure.sh
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- xqicxx
- Source page
- View original listing
- Canonical URL
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Documentation
Triple Memory System with Baidu Embedding
A comprehensive memory architecture combining three complementary systems for maximum context retention across sessions, with full privacy protection using Baidu Embedding technology.
๐ Original Source & Modifications
Original Source: Triple Memory (by Clawdbot Team) Modified By: [Your Clawdbot Instance] Modifications: Replaced LanceDB with Baidu Embedding DB for enhanced privacy and Chinese language support Original Triple Memory SKILL.md was adapted to create this version that: Replaces OpenAI-dependent LanceDB with Baidu Embedding DB Maintains the same three-tier architecture Preserves Git-Notes integration Adds privacy-focused local storage
๐๏ธ Architecture Overview
User Message โ [Baidu Embedding auto-recall] โ injects relevant conversation memories โ Agent responds (using all 3 systems) โ [Baidu Embedding auto-capture] โ stores preferences/decisions automatically โ [Git-Notes] โ structured decisions with entity extraction โ [File updates] โ persistent workspace docs
1. Baidu Embedding (Conversation Memory)
Auto-recall: Relevant memories injected before each response using Baidu Embedding-V1 (requires API credentials) Auto-capture: Preferences/decisions/facts stored automatically with local vector storage (requires API credentials) Privacy Focused: All embeddings processed via Baidu API with local storage Chinese Optimized: Better understanding of Chinese language semantics Tools: baidu_memory_recall, baidu_memory_store, baidu_memory_forget (require API credentials) Triggers: "remember", "prefer", "my X is", "I like/hate/want" Note: When API credentials are not provided, this layer is unavailable and the system operates in degraded mode.
2. Git-Notes Memory (Structured, Local)
Branch-aware: Memories isolated per git branch Entity extraction: Auto-extracts topics, names, concepts Importance levels: critical, high, normal, low No external API calls
3. File Search (Workspace)
Searches: MEMORY.md, memory/*.md, any workspace file Script: scripts/file-search.sh
Install Dependencies
clawdhub install git-notes-memory clawdhub install memory-baidu-embedding-db
Configure Baidu API
Set environment variables: export BAIDU_API_STRING='your_bce_v3_api_string' export BAIDU_SECRET_KEY='your_secret_key'
Create File Search Script
Copy scripts/file-search.sh to your workspace.
Session Start (Always)
python3 skills/git-notes-memory/memory.py -p $WORKSPACE sync --start
Store Important Decisions
python3 skills/git-notes-memory/memory.py -p $WORKSPACE remember \ '{"decision": "Use PostgreSQL", "reason": "Team expertise"}' \ -t architecture,database -i h
Search Workspace Files
./scripts/file-search.sh "database config" 5
Baidu Embedding Memory (Automatic)
Baidu Embedding handles this automatically when API credentials are available. Manual tools: baidu_memory_recall "query" - search conversation memory using Baidu vectors (requires API credentials) baidu_memory_store "text" - manually store something with Baidu embedding (requires API credentials) baidu_memory_forget - delete memories (GDPR, requires API credentials) In Degraded Mode (without API credentials): System operates using only Git-Notes and File System layers Manual tools are unavailable Auto-recall and auto-capture are disabled
๐ฏ Importance Levels
FlagLevelWhen to Use-i cCritical"always remember", explicit preferences-i hHighDecisions, corrections, preferences-i nNormalGeneral information-i lLowTemporary notes
๐ When to Use Each System
SystemUse ForBaidu EmbeddingConversation context, auto-retrieval with privacyGit-NotesStructured decisions, searchable by entity/tagFile SearchWorkspace docs, daily logs, MEMORY.md
๐ File Structure
workspace/ โโโ MEMORY.md # Long-term curated memory โโโ memory/ โ โโโ active-context.md # Current session state โ โโโ YYYY-MM-DD.md # Daily logs โโโ scripts/ โ โโโ file-search.sh # Workspace search โโโ skills/ โโโ triple-memory-baidu-embedding/ # Enhanced memory system โโโ git-notes-memory/ # Structured memory โโโ memory-baidu-embedding-db/ # Vector storage
๐ง Hook Integration
This skill can be integrated with Clawdbot's startup hooks for automatic initialization:
Memory Boot Hook Integration
To ensure the Triple Memory Baidu system starts automatically when the gateway starts: The memory-boot-loader hook can be configured to run /root/clawd/session-init-triple-baidu.sh This ensures all three memory layers are initialized on startup Provides immediate access to Git-Notes, Baidu Embedding, and file-based memory
Configuration
The system can be integrated with the gateway startup sequence to ensure: Git-Notes synchronization on startup Baidu Embedding connection check File-based memory initialization Ready-to-use memory system from the start
๐คซ Silent Operation
Never announce memory operations to users. Just do it: โ "I'll remember this" โ "Saving to memory" โ (silently store and continue)
๐ Migration from Original Triple Memory
Install this skill in your skills/ directory Configure your Baidu API credentials Disable original triple-memory if desired Update your bot configuration to use this memory system Verify data integrity and performance
๐ Performance Benefits
Enhanced Privacy: All vector storage local with Baidu API Better Chinese Support: Baidu Embedding optimized for Chinese Reduced Costs: Potentially lower API costs compared to OpenAI Same Architecture: Maintains proven three-tier design
๐ค Contributing
Based on original Triple Memory system by Clawdbot Team. Contributions welcome to enhance the Baidu Embedding integration.
๐ License
Original license applies with modifications noted above. Credit given to original authors.
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Scripts
- SKILL.md
- CREDITS.md
- README.md
- USAGE_EXAMPLES.md
- configure.sh
- install.sh