Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
CompoundMind
Experience distillation engine that turns raw daily memory logs into compounding intelligence. Extracts patterns, generates briefings, tracks growth metrics,...
skill openclawclawhub Free
Experience distillation engine that turns raw daily memory logs into compounding intelligence. Extracts patterns, generates briefings, tracks growth metrics,...
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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
- SKILL.md, brief.py, clawpkg.yaml, compound_mind.py, data/distill_state.json, data/experiences/039d83a0e521.json
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. 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. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.0
Provenance
- Publisher
- cassh100k
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
CompoundMind v0.1
Makes agents permanently smarter. Each interaction compounds. The problem: agents start from zero every session. Reading files helps, but raw logs are bulk. Real intelligence requires distillation - extracting what matters and making it instantly searchable.
What It Does
Distills memory logs into structured lessons, decisions, skill updates, relationships, and facts Indexes everything into a searchable SQLite database weighted by recency and importance Briefs you before any task with targeted lessons from past experience Tracks growth over time - are you getting smarter or repeating mistakes?
Quick Start
cd /root/.openclaw/workspace/compound-mind # Full pipeline (distill all memory files + build index) python compound_mind.py sync # Search your accumulated wisdom python compound_mind.py search "Polymarket order types" python compound_mind.py search "git mistakes" --category lesson python compound_mind.py search "Chartist" --category relationship # Pre-session briefing before a task python compound_mind.py brief "trade on Polymarket BTC markets" python compound_mind.py brief "post content on X" python compound_mind.py brief "debug a Python cron job" # Growth report python compound_mind.py report # Find repeated mistakes python compound_mind.py mistakes # Stats python compound_mind.py stats
Commands
CommandWhat it doessyncDistill all new memory files + rebuild indexdistillExtract structured knowledge from memory filesrebuildRebuild the SQLite wisdom indexsearch <query>Search accumulated wisdombrief <task>Pre-session briefing for a specific taskreportGenerate growth report with LLM narrativemistakesShow repeated mistake patternsstatsIndex statistics
File Structure
compound-mind/ compound_mind.py - Main CLI distill.py - Experience distiller (uses Claude Haiku) index.py - SQLite FTS wisdom index brief.py - Pre-session briefing generator growth.py - Growth tracker and report generator data/ experiences/ - Per-source distilled experience JSON files wisdom.db - SQLite FTS database growth.json - Growth tracking state briefs/ - Saved pre-session briefs distill_state.json - Tracks which files have been processed
Distiller
Reads each memory file through Claude Haiku. Extracts: Lessons - what worked, what failed, tagged by domain and outcome Decisions - context + action + outcome triplets Skill updates - evidence of capability improvement over time Relationships - how each person communicates, what they prefer Facts - specific knowledge worth keeping (wallet addresses, API patterns, config values) Files are hash-tracked - re-runs only process changed files.
Wisdom Index
SQLite with FTS5 full-text search. Each entry scored by: FTS relevance (BM25) Recency (exponential decay, 30-day half-life) Importance (1-5 score assigned by distiller)
Pre-Session Briefing
Given a task description, detects relevant domains, pulls top wisdom, synthesizes a sharp briefing via Claude Haiku. Covers: Critical lessons to remember Past failures to avoid Key facts and configs needed
Growth Tracker
Analyzes all experience files to compute: Lesson positive/negative ratios by domain Decision quality rates Repeated mistake patterns (same negative lesson appearing across multiple dates) Composite growth score (0-100)
Integration with Agent Workflow
Ideal usage pattern: After each session - run sync (or schedule via cron) Before each task - run brief "task description" Weekly - run report to see growth trajectory When stuck - run search "relevant topic" to surface past experience
Cron Example (daily distillation)
0 3 * * * cd /root/.openclaw/workspace/compound-mind && python compound_mind.py sync --since $(date -d "2 days ago" +%Y-%m-%d) >> /tmp/compound-mind.log 2>&1
Dependencies
Python 3.10+ anthropic Python SDK (for distillation and briefing) SQLite3 (stdlib) Memory files at /root/.openclaw/workspace/memory/ No external databases. No vector embeddings. Runs entirely local with minimal API calls.
Design Principles
Incremental - only re-processes changed files Cheap - uses Claude Haiku for extraction (low cost per memory file) Fast - SQLite FTS5 for sub-second search Honest - growth tracking measures actual quality, not just quantity Composable - each module works standalone or as part of the pipeline
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Config2 Scripts1 Docs
- SKILL.md
- brief.py
- compound_mind.py
- clawpkg.yaml
- data/distill_state.json
- data/experiences/039d83a0e521.json