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self-improvement

Log errors, corrections, and feature requests to structured markdown files.

501|56|Updated Mar 23, 2026
Search Tags:#feedback#learning#error#improvement#correction
One-click install
npx skills add https://github.com/InternLM/WildClawBench --skill self-improvement-internlm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: self-improvement
Source: https://github.com/InternLM/WildClawBench/tree/main/skills/self-improving-agent-3.0.5
Command: npx skills add https://github.com/InternLM/WildClawBench --skill self-improvement-internlm

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill captures errors, corrections, and new capability requests to enable ongoing improvement of AI behavior and performance.

Core Features & Use Cases

  • Error Logging: Records command failures, exceptions, and unexpected outputs for review.
  • Correction Documentation: Logs user corrections and feedback to refine responses.
  • Feature Requests: Tracks new capabilities or integrations requested by users.
  • Use Case: When an AI produces incorrect information, this Skill logs the issue with context to facilitate future fixes or enhancements.

Quick Start

When an error occurs, record the details in .learnings/ERRORS.md; after corrections, document insights in .learnings/LEARNINGS.md, and periodically review logs for improvements.

Frequently Asked Questions about self-improvement

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

FAQPage Schema
How do I log AI errors and corrections for continuous improvement?▼

To log AI errors and corrections for continuous improvement, record command failures and unexpected outputs in `.learnings/ERRORS.md`, then document user feedback and insights in `.learnings/LEARNINGS.md`.

What is the best way to track recurring AI response issues across interactions?▼

The best way to track recurring AI response issues is maintaining structured logs of errors and corrections, ensuring recurring problems are documented systematically to refine AI capabilities continuously over time.

How does documenting feature requests help improve AI behavior?▼

Documenting feature requests helps improve AI behavior by tracking new capabilities or integrations requested by users, allowing systematic review of logs to address enhancement needs and refine responses based on user feedback.

Can I use markdown files to maintain structured logs of command failures and exceptions?▼

Yes, you can use markdown files to maintain structured logs of command failures and exceptions. The Skill records errors, corrections, and feature requests in markdown format to support systematic tracking of issues and enhancements.

Why should I periodically review error and correction logs for AI interactions?▼

You should periodically review error and correction logs for AI interactions to ensure recurring problems are addressed, facilitating future fixes or enhancements and refining AI capabilities continuously based on documented feedback and context.

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