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name: compound-mind description: Experience distillation engine that turns raw daily memory logs into compounding intelligence. Extracts patterns, generates briefings, tracks growth metrics, and builds a searchable experience index. Agents get permanently smarter - each interaction compounds into wisdom. Use when you want agents that learn from their history instead of starting fresh every session.

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

1. Distills memory logs into structured lessons, decisions, skill updates, relationships, and facts
2. Indexes everything into a searchable SQLite database weighted by recency and importance
3. Briefs you before any task with targeted lessons from past experience
4. 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

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

How It Works

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:

1. After each session - run sync (or schedule via cron)
2. Before each task - run brief "task description"
3. Weekly - run report to see growth trajectory
4. 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