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Skillshub capy-cortex

Autonomous learning system - learns from mistakes, reflects on sessions, and gets smarter over time. The AI brain.

install
source · Clone the upstream repo
git clone https://github.com/ComeOnOliver/skillshub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/ComeOnOliver/skillshub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/happycapy-ai/Happycapy-skills/capy-cortex" ~/.claude/skills/comeonoliver-skillshub-capy-cortex && rm -rf "$T"
manifest: skills/happycapy-ai/Happycapy-skills/capy-cortex/SKILL.md
source content

Capy Cortex - Autonomous Learning System

You have a persistent learning brain powered by SQLite + FTS5 + sklearn TF-IDF. Knowledge is automatically loaded via hooks. This file describes manual operations.

Architecture

  • Database: 
    ~/.claude/skills/capy-cortex/cortex.db
    (SQLite + FTS5 + WAL)
  • Hooks (automatic, never call manually):
    • SessionStart: Loads anti-patterns, preferences, principles
    • UserPromptSubmit: Retrieves task-relevant rules via FTS5
    • PreToolUse(Bash): Blocks known dangerous commands
    • PostToolUseFailure: Records errors as anti-patterns
    • Stop: Extracts corrections and preferences from conversation
  • Scripts (for manual/scheduled use): 
    • cortex.py
      : Core engine (retrieve, add rules, stats)
    • reflect.py
      : Deep session analysis
    • consolidate.py
      : Cluster rules into principles (sklearn)
    • bootstrap.py
      : Mine historical sessions

Manual Commands

# Check system health
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py stats

# Retrieve rules for a topic
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py retrieve "react typescript"

# Add a rule manually
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-rule "Always use TypeScript strict mode" "best_practice"

# Add an anti-pattern
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-ap "Never force push to main" "critical"

# Add a preference
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py add-pref "User prefers functional components over class components"

# Run consolidation (clusters rules into principles)
python3 ~/.claude/skills/capy-cortex/scripts/consolidate.py

# Retrain TF-IDF model
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py retrain

# Apply confidence decay
python3 ~/.claude/skills/capy-cortex/scripts/cortex.py decay

How It Learns

  1. Automatic (via hooks): Errors are captured, corrections noted, preferences extracted
  2. Reflection: Deep analysis of session transcripts extracts patterns
  3. Consolidation: sklearn clustering groups similar rules into principles
  4. Decay: Old, unreinforced rules fade; validated rules strengthen
  5. Retrieval: Two-stage FTS5 + TF-IDF returns only relevant knowledge (O(1) context)