Analyze runtime history and apply GEP protocol-constrained changes to AI agents.
npx skills add https://github.com/autogame-17/evolver --skill capability-evolver
Please help me install this Agent Skill. Skill: capability-evolver Source: https://github.com/autogame-17/evolver/tree/main Command: npx skills add https://github.com/autogame-17/evolver --skill capability-evolver
The Capability Evolver analyzes runtime history to identify failures, inefficiencies, and opportunities for safe, auditable evolution of AI agents.
Run node index.js to start the evolution cycle.
High-intent search queries and answers about installing and using this skill.
Auditable self-evolution for AI agents is achieved by analyzing runtime history to identify improvements and applying protocol-constrained changes. The engine emits EvolutionEvents and stores assets as reusable records for governance and compliance.
The GEP protocol enforces deterministic mutations by emitting a Mutation, a PersonalityState, and an EvolutionEvent. It uses safety checks to ensure reproducible improvements during the agent evolution loop.
You can harden AI agent loops by using auto-log analysis to scan runtime logs and memory. This surfaces actionable signals of failures and inefficiencies to trigger safe, protocol-constrained evolution.
Yes, the deterministic evolution loop supports mad-dog continuous running mode alongside explicit review modes. Both ensure reproducible improvements while enforcing safety checks on every mutation.
You encode fixes as reusable assets by storing genes, capsules, and EvolutionEvents through the GEP protocol. This creates auditable records that capture governance changes across AI agents.
mpelissariAnalyze runtime history and apply safe mutations to patch agent inefficiencies.
jovermierAnalyze repository commit history to trace code evolution and ownership.
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vltanskyStart a log server and analyze runtime logs to debug applications.
