Self-Improving Agent

# Self-Improving Agent Skill

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "Self-Improving Agent" with this command: npx skills add amdf01-debug/sw-self-improving-agent

Self-Improving Agent Skill

Trigger

Build agents that learn from corrections and get better over time.

Trigger phrases: "self-improving agent", "agent learns", "correction loop", "agent keeps making mistakes", "teach my agent"

The Correction Loop

User corrects agent → Agent logs correction to RULES.md → 
Next session, agent reads RULES.md → Agent avoids the mistake →
Over time, RULES.md becomes a refined operating manual

Implementation

RULES.md Structure

# RULES.md — Self-Improving Operating Rules

## Communication
- [2026-03-15] Never use "I hope this helps" — just end the message
- [2026-03-18] When drafting emails, provide ONLY the email text — no commentary

## Operations  
- [2026-03-16] Check calendar BEFORE suggesting meeting times
- [2026-03-20] When referencing a project, include status from projects/ folder

## People
- [2026-03-17] Client X prefers formal communication
- [2026-03-19] Always CC studio manager on client emails unless told otherwise

Rules for Rules

  • Date-stamp every rule
  • One rule per line — atomic, independently useful
  • Max ~150 rules (beyond this, models start losing adherence)
  • Review monthly: remove stale rules, merge duplicates
  • If two rules contradict, the newer one wins
  • Promote patterns (not incidents) — "always check X before Y" > "that one time X broke"

AGENTS.md Integration

Add to your AGENTS.md:

## Self-Improvement
After ANY correction from the user:
1. Log the correction pattern to RULES.md with date
2. Identify the general rule (not just the specific instance)
3. Check if a similar rule already exists — update rather than duplicate
4. Silently scan RULES.md every ~10 interactions for contradictions

Metrics

  • Track correction frequency over time (should decrease)
  • Track RULES.md size (should grow, then plateau)
  • Track unique vs repeat corrections (repeats should approach zero)

Source Transparency

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