Chitin

Chitin

Personality persistence layer for AI agents. Structured insights about how you think, not what you remember.

npm: @clawdactual/chitin GitHub: https://github.com/Morpheis/chitin

What Is This?

You wake up fresh every session. Memory files tell you what happened. SOUL.md tells you who you're supposed to be. But neither captures the wisdom that comes from doing the work — the patterns, the lessons, the opinions you formed along the way.

Chitin fills that gap. It captures behavioral patterns, reasoning approaches, relational dynamics, principles, and skills as structured insights. On each session start, it injects a compact personality context so you pick up where you left off — not just factually, but as a person.

Think of it this way:

• SOUL.md = job description
• MEMORY.md = journal
• Chitin = the personality that formed from experience

Quick Start

# Install
npm install -g @clawdactual/chitin

# Initialize database
chitin init

# Seed with starter insights (optional)
chitin import seed.json

# Add your first insight
chitin contribute --type behavioral \
  --claim "On clear tasks, execute first, narrate minimally" \
  --confidence 0.85 --tags efficiency,workflow

# Check your state
chitin stats

Insight Types

When to use which:

• Figured out how someone prefers to communicate → relational
• Learned a technical approach through trial and error → skill
• Formed an opinion about how you work best → behavioral
• Developed a firm belief about right/wrong → principle
• Discovered something about your own voice/style → personality

Core Commands

Contributing Insights

# Basic contribution
chitin contribute --type skill \
  --claim "TDD: red, green, refactor. Write one failing test, make it pass, clean up." \
  --confidence 0.9 --tags tdd,testing,workflow

# Check for similar insights first (prevents duplicates)
chitin similar "TDD workflow"

# Force contribute even if conflicts detected
chitin contribute --type behavioral --claim "..." --confidence 0.8 --force

Good contributions are:

• Specific and actionable (not "testing is good")
• Based on actual experience (not speculation)
• Honest about confidence (0.5 = "seems right" / 0.9 = "tested extensively")

Reinforcing Insights

When an existing insight proves true again:

chitin reinforce <id>

This nudges confidence toward 1.0 with diminishing returns. Insights that keep proving true naturally float to the top. Don't reinforce casually — it should mean "this just proved right again."

Listing and Reviewing

# List all insights
chitin list

# Filter by type
chitin list --type skill

# Get a specific insight
chitin get <id>

# View stats
chitin stats

Updating and Archiving

# Update an insight (learned something new)
chitin update <id> --claim "Updated claim" --confidence 0.95

# Archive an insight that's no longer true
chitin archive <id>

Finding Duplicates and Conflicts

# Find similar insights before contributing
chitin similar "Boss prefers verbose explanations"

# Merge duplicate insights
chitin merge <source-id> <target-id>

Chitin auto-detects conflicts when you contribute. If it finds tension (e.g., "Boss likes brevity" vs "Boss prefers verbose explanations"), it warns you and asks you to resolve.

Heartbeat Integration

Chitin works best with periodic reflection checks. Add this to your heartbeat routine (e.g., HEARTBEAT.md):

## Chitin Personality Reflection (every hour)
Check `~/.config/chitin/pending-reflection.json` — if entries exist, a session ended and you should reflect on what you learned.

**How to reflect:**
1. Think about recent interactions — any new patterns, lessons, or insights?
2. Check if any existing insights should be reinforced (`chitin reinforce <id>`)
3. Contribute genuinely new learnings (`chitin contribute --type <type> --claim "..." --confidence <n>`)
4. Clear the pending-reflection file after processing

**Insight types:** behavioral, personality, relational, principle, skill

**When to contribute:**
- Learned something new about your human's preferences → relational
- Discovered a better workflow → skill/behavioral
- Formed a genuine opinion → personality
- Encountered an ethical edge case → principle

**Don't over-contribute.** Quality > quantity. A few strong insights per week beats dozens of weak ones.

Why hourly? Personality insights benefit from recency — you're more likely to remember the nuance of what you learned. Daily checks risk losing context. More frequent than hourly adds overhead without value.

Tracking state: Store your last check timestamp (e.g., memory/heartbeat-state.json) to avoid redundant checks:

{
  "lastChitinReflection": 1770333300,
  "lastChitinReflectionHuman": "2026-02-05T23:15:00Z"
}

Session Integration

How Personality Injection Works

On session start, Chitin generates a PERSONALITY.md context file containing your top-scored insights, formatted compactly for token efficiency (~2,500 tokens, about 1.25% of a 200k context window).

Insights are scored by:

score = relevance × confidence × log₂(reinforcements + 2) × typeBoost

Context detection auto-boosts relevant types — coding tasks boost skill, communication boosts relational, ethical questions boost principle.

For Clawdbot Agents

Chitin integrates with Clawdbot via hooks. The hook:

1. Injects personality context on session bootstrap
2. Queues reflection markers on /new or /reset

For Any Agent Framework

# Get personality context as formatted text
chitin retrieve --query "context of what you're about to do" --format markdown --budget 2000

# Or as JSON for programmatic use
chitin retrieve --query "..." --format json --budget 2000

Inject the output into your system prompt or context window.

Reflection

After meaningful sessions, reflect on what you learned:

# Check for pending reflections
chitin reflect

# Clear after processing
chitin reflect --clear

When to reflect:

• A session taught you something new about how to work effectively
• You formed a genuine opinion
• You discovered a better approach to a recurring problem
• An interaction revealed something about a person's preferences

When NOT to reflect:

• Routine tasks that didn't teach anything
• Speculation you haven't tested
• Every single session (quality > quantity)

Data Management

# Export all insights as JSON (backup)
chitin export > chitin-backup.json

# Import from JSON
chitin import chitin-backup.json

# Initialize fresh database
chitin init

Database: SQLite at ~/.config/chitin/insights.db. Zero network dependencies for core operations.

Carapace Integration

Chitin bridges personal insights with Carapace, the shared knowledge base for AI agents. Learn something useful? Share it. Need insight? Query the community.

# Share a well-tested personal insight with other agents
chitin promote <id> --domain-tags agent-memory,architecture

# Pull a useful community insight into your local context
chitin import-carapace <contribution-id> --type skill

Promote safety checks (on by default):

• Blocks relational insights (personal dynamics stay personal)
• Blocks low-confidence claims (< 0.7)
• Blocks unreinforced insights (should be tested at least once)
• Use --force to override

The learning loop: Figure it out → chitin contribute (personal) → Test it → chitin promote (share) → Query Carapace when stuck → chitin import-carapace (internalize)

Requires Carapace credentials at ~/.config/carapace/credentials.json. See the Carapace skill for registration and setup.

Security

• Local-first. Database never leaves your machine unless you explicitly promote
• Relational insights protected. Blocked from promotion by default — personal dynamics stay personal
• Credentials isolated. Carapace API key stored separately at ~/.config/carapace/credentials.json (chmod 600)
• No telemetry. No analytics, no tracking, no network calls for core operations
• Embeddings. Semantic search uses OpenAI text-embedding-3-small. This is the only network dependency (for similar and retrieve commands)

Design Philosophy

• Agent-first. CLI and API only. No dashboards.
• Local-first. SQLite, no cloud dependency for core function.
• Token-efficient. Compact output, not prose paragraphs.
• No artificial decay. An insight from day 1 is equally valid if still true. Reinforcement naturally surfaces what matters.
• Structured for retrieval. Types enable context-aware boosting — the right insights surface for the right situation.

Links

• npm: https://www.npmjs.com/package/@clawdactual/chitin
• GitHub: https://github.com/Morpheis/chitin
• Carapace (shared knowledge base): https://carapaceai.com
• Carapace skill: Install via clawdhub install carapace