What is a skill evolution ecosystem?

It is a framework where AI skills are treated as evolving entities that improve over time based on performance data, usage statistics, and automated validation.

When does a skill face extinction?

Skills are deprecated if they fail validation for multiple generations, have zero activations over a 90-day period, or are superseded by more efficient platform-native features.

Does this skill support cross-platform agents?

Yes, it includes built-in validators for various platforms including Claude Code and Codex, ensuring skills remain functional as agent platforms evolve.

What are mutation operators in this context?

Mutation operators are specific refinement actions such as clarifying skill descriptions, compressing the skill body for efficiency, or rebalancing mathematical triads for better composition.

How are skill fitness metrics calculated?

Fitness is measured via compatibility scores across multiple platforms, activation frequency in real-world tasks, and token efficiency (the ratio of task success to tokens used).

Skill Evolution & Optimization

Name: Skill Evolution & Optimization
Author: plurigrid

byplurigrid

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Developer Tools

Implements Darwin-Gödel principles to create self-improving, evolutionarily robust skill ecosystems for AI agents.

Skill Evolution provides a framework for managing a 'living' repository of AI capabilities by applying evolutionary pressure and rigorous fitness metrics. It allows developers to maintain a high-performing ecosystem of skills through automated mutation, selection based on usage data, and cross-platform validation. By measuring token efficiency, activation rates, and GF(3) compositional coherence, it ensures that only the most effective, concise, and compatible patterns survive across successive agent generations.

Key Features

01Speciation management for splitting monolithic skills into specialized modules

02Automated mutation operators for description refinement and body compression

03Natural and artificial selection protocols for skill retention or deprecation

04Fitness metric tracking including token efficiency and activation rates

05GF(3) balanced triad integration for ensuring compositional coherence

062 GitHub stars

Use Cases

01Automating the lifecycle management and deprecation of redundant code patterns

02Ensuring cross-platform compatibility across different LLM agent implementations and MCP servers

03Optimizing a large library of AI agent skills for maximum performance and minimum token cost

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add plurigrid/asi skill-evolution

For use in Claude.ai and ChatGPT

Download Skill