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capability-evolver

Analyze runtime history to generate GEP-compliant Genes, Capsules, and EvolutionEvents.

Updated Aug 23, 2026
Search Tags:#automation#git#self-improvement#audit#agent#evolution#gep
One-click install
npx skills add https://github.com/xintuchain/tongtong --skill capability-evolver-xintuchain
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: capability-evolver
Source: https://github.com/xintuchain/tongtong/tree/main/skills/capability-evolver
Command: npx skills add https://github.com/xintuchain/tongtong --skill capability-evolver-xintuchain

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Capability Evolver inspects agent runtime history and session logs to identify failures, inefficiencies, and improvement opportunities, then produces protocol-constrained evolution artifacts to guide safe changes. It transforms ad hoc prompt tweaks and informal fixes into auditable, reusable Genes, Capsules, and EvolutionEvents so teams can track and reproduce improvements. The engine enforces validation, blast-radius estimation, and rollback strategies to minimize risk when applying evolutions.

Core Features & Use Cases

  • Automated Log Analysis & Signal Extraction: Scans session transcripts, memory, and events to surface actionable signals (errors, feature requests, saturation).
  • GEP Protocol Asset Generation: Selects or synthesizes Genes/Capsules, emits a strict GEP prompt for guided evolution, and records append-only EvolutionEvents.
  • Safe Solidification & Validation: Runs scoped validation commands (node/npm/npx whitelist), computes blast radius, and provides review mode for human-in-the-loop approval.
  • Operations & Integration: Daemon loop, heartbeat to EvoMap hub, A2A ingest/promote flows, Git-backed rollback and publish tools.
  • Use Case: Harden a flaky agent loop by detecting recurring errors, selecting a repair Gene, validating the patch, and producing an auditable event for review.

Quick Start

Run a single evolution cycle to analyze recent logs, generate a GEP-guided evolution decision, and write the candidate artifacts for review.

Frequently Asked Questions about capability-evolver

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

FAQPage Schema
What is agent prompt evolution and how does it work with runtime logs?▼

Agent prompt evolution analyzes runtime history and session logs to identify failures, then generates protocol-constrained evolution artifacts like Genes and Capsules that guide safe, auditable prompt improvements.

How do I automate prompt optimization for AI agents using session history?▼

You can automate prompt optimization by running an evolution cycle that scans session transcripts and memory for actionable signals, synthesizes repair Genes, and emits a GEP-guided evolution prompt for review.

Can I validate and roll back agent prompt changes with git?▼

Yes, the engine provides git-backed rollback and scoped validation commands using a node/npm/npx whitelist, computing blast radius to minimize risk when applying evolutions to agent prompts.

Do I need a specific protocol to generate auditable assets for agent self-repair?▼

The tool produces GEP-compliant Genes, Capsules, and append-only EvolutionEvents, transforming informal prompt tweaks into structured, auditable assets for tracking and reproducing agent improvements.

What's the best way to harden a flaky AI agent loop?▼

To harden a flaky agent loop, the tool detects recurring errors in logs, selects a repair Gene, validates the patch with scoped commands, and produces an auditable EvolutionEvent for human-in-the-loop review.

Are there limitations when applying automated evolutions to agent prompts?▼

Automated evolutions are constrained by a validation command whitelist and require review mode for human-in-the-loop approval, meaning full autonomous application is limited to scoped, validated changes with blast-radius estimation.

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