evo

Capture and classify lessons learned from AI agent usage.

Updated May 17, 2026
One-click install
npx skills add https://github.com/ievo-ai/skills --skill evo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: evo
Source: https://github.com/ievo-ai/skills/tree/main/plugins/ievo/skills/evo
Command: npx skills add https://github.com/ievo-ai/skills --skill evo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gh, git, and includes scripts (resource) and references (resource) components.

What problem does it solve?

The 'evo' skill solves the problem of documenting and tracking lessons learned from using AI agents or skills, allowing for continuous improvement and evolution of the AI systems.

Core Features & Use Cases

  • Lesson Capture: Allows users to capture lessons learned when working with AI agents or skills.
  • Scope Classification: Automatically classifies lessons as project-wide, agent-specific, or skill-specific.
  • Overlay File Management: Manages the creation and modification of overlay files for different scopes.
  • Upstream Feedback: Offers the option to share lessons with the iEvo plugin repository for improvement.

Quick Start

After completing an AI session, type: /evo:capture "Remember to always validate user inputs before processing" to add a lesson for improvement.

Frequently Asked Questions about evo

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

FAQPage Schema
How do I capture lessons learned from AI agent sessions for continuous improvement?

You capture lessons learned from AI agent sessions by invoking a capture command to log insights, which automatically classifies them as project-wide, agent-specific, or skill-specific for continuous improvement.

What is the best way to document AI agent evolution and track system improvements?

Documenting AI agent evolution involves creating and modifying overlay files based on captured lessons, enabling you to track system improvements and apply them to project management workflows.

Do I need git and gh CLI installed to manage AI skill evolution and feedback?

Yes, you need git and gh CLI installed to manage AI skill evolution, as the system requires gh CLI for fetching API metadata and git for cloning repositories to support upstream feedback.

Can I share captured AI lessons with an upstream repository for plugin improvement?

Yes, you can share captured AI lessons with an upstream repository, as the system offers an option to submit feedback directly to the iEvo plugin repository for broader plugin improvement.

How does scope classification work when tracking AI project management lessons?

Scope classification for AI project management lessons works by automatically categorizing each captured insight into project-wide, agent-specific, or skill-specific scopes to ensure targeted system improvement.

Why are my overlay files not updating after capturing AI agent lessons?

Overlay files may not update after capturing AI agent lessons if the scope classification fails or if prerequisite tools like gh CLI and git are not properly configured in your environment.