self-improvement

Log learnings and corrections to markdown files for AI coding agents.

Updated Mar 23, 2026
One-click install
npx skills add https://github.com/binfen1/my-skills --skill self-improvement-binfen1
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: self-improvement
Source: https://github.com/binfen1/my-skills/tree/main/openclaw/self-improving-agent
Command: npx skills add https://github.com/binfen1/my-skills --skill self-improvement-binfen1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Logs learnings, errors, and corrections to enable continuous improvement for AI agents by logging them to markdown files for later processing and memory promotion.

Core Features & Use Cases

  • Log learnings to .learnings/LEARNINGS.md, .learnings/ERRORS.md, and .learnings/FEATURE_REQUESTS.md
  • Promote broadly applicable learnings to CLAUDE.md, AGENTS.md, and/or SOUL/TOOLS when appropriate
  • OpenClaw workflow: workspace prompts, hooks, and inter-session sharing to spread knowledge
  • Use when errors occur, corrections happen, or new capabilities are requested; maintain an evolving knowledge base

Quick Start

Log learnings immediately after events using the provided templates.

Frequently Asked Questions about self-improvement

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I log errors and corrections to enable continuous improvement for AI coding agents?

To enable continuous improvement for AI coding agents, log errors and corrections to markdown files within the .learnings directory. This captures failures and user corrections across OpenClaw sessions for later processing and memory promotion.

What is a learning log for AI agents and how does it work?

A learning log for AI agents records failures, user corrections, and feature requests into structured markdown files. It works by capturing these events across OpenClaw sessions, enabling workspace-wide memory propagation and continuous improvement.

Do I need a specific directory structure to track AI agent learnings?

Yes, tracking AI agent learnings requires a .learnings directory structure containing LEARNINGS.md, ERRORS.md, and FEATURE_REQUESTS.md files. Optional promotion targets like CLAUDE.md and AGENTS.md can also be configured.

When should I promote captured learnings to workspace memory files?

You should promote captured learnings to workspace memory files like CLAUDE.md, AGENTS.md, or SOUL/TOOLS when the knowledge is broadly applicable. This ensures workspace-wide memory propagation for AI agents.

Can I use hook integration to automate knowledge management across OpenClaw sessions?

Yes, you can use OpenClaw hook integration to automate knowledge management across sessions. Hooks help spread knowledge and log learnings immediately after events occur, maintaining an evolving knowledge base.

What is the best way to maintain an evolving knowledge base for AI coding agents?

The best way to maintain an evolving knowledge base for AI agents is logging learnings, errors, and feature requests to markdown files. This enables inter-session sharing and promotes broadly applicable knowledge to workspace memory files.