self-evolution-module

What problem does it solve?

This Skill solves repeated agent failures by forcing a structured reflection-driven retry loop that evolves the prompt, tools, and workflow based on observed outcomes instead of cosmetic changes.

Core Features & Use Cases

• Prompt evolution to sharpen success conditions, refine framing, and better decompose tasks when understanding or instructions are the bottleneck.
• Tool evolution to improve observability, add specialized helpers, or wrap/replace tool interfaces when execution is brittle or inefficient.
• Workflow evolution to change the process graph (gates, verifiers, sequencing, or parallel branches) when sequencing or missing checks cause instability.
• Use case: An agent repeatedly produces incomplete solutions because required acceptance criteria are not actually verified; this Skill drives attempt-by-attempt redesign until the acceptance gate is satisfied.

Quick Start

Ask the agent to run a reflection-driven retry loop for the task, using the attempt cap (default 5) and only stopping when the task’s explicit acceptance gate is met.