skill-evolution-manager

Merge user feedback into evolution.json and SKILL.md documentation.

4|Updated Jan 22, 2026

Search Tags:#automation #documentation #skill management #feedback loop #continuous improvement #AI evolution

Ready to run

npx skills add https://github.com/oiiiwjh/skills --skill skill-evolution-manager-oiiiwjh

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill-evolution-manager
Source: https://github.com/oiiiwjh/skills/tree/main/skill-evolution-manager
Command: npx skills add https://github.com/oiiiwjh/skills --skill skill-evolution-manager-oiiiwjh

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill streamlines the process of improving AI skills by systematically collecting, processing, and integrating user feedback and observed performance into the skill's documentation and logic.

Core Features & Use Cases

Automated Feedback Integration: Captures user preferences, fixes, and custom prompts from conversations.
Skill Documentation Enhancement: Automatically updates SKILL.md with learned best practices and constraints.
Use Case: After a user struggles with a specific parameter in a skill, this tool can record the correct usage or a workaround, ensuring future interactions with that skill are smoother.

Quick Start

Use the skill-evolution-manager to record user preferences for the github-commit skill.

Frequently Asked Questions about skill-evolution-manager

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

FAQPage Schema

How do I automate AI skill improvement using user feedback?▼

Automating AI skill improvement involves capturing user feedback and dialogue analysis to update skill documentation automatically. This Skill merges those insights into evolution.json and stitches learned best practices directly into SKILL.md files.

How does automated documentation update work for continuous skill evolution?▼

Automated documentation update works by running Python scripts that merge user feedback into evolution.json, then stitching those learned constraints and workarounds directly into SKILL.md. This ensures skill documentation reflects real-time performance.

Can I use Python scripts to integrate user preferences into skill management?▼

Yes, you can use Python scripts to integrate user preferences into skill management. The scripts process dialogue analysis and merge captured fixes or custom prompts into evolution.json, persistently storing learned best practices.

What is the best way to record workarounds when users struggle with skill parameters?▼

The best way to record workarounds is to capture the correct usage or fixes from the conversation dialogue. This Skill systematically integrates those user preferences into the skill's logic, ensuring smoother future interactions.

Do I need any dependencies to run the skill evolution manager?▼

No dependencies are required to run the skill evolution manager. It operates independently using internal Python scripts to process feedback, update evolution.json, and enhance your existing SKILL.md documentation.