Skill UI

This tool executes a GEPA learning cycle, automating the evolution and optimization of policy prompts against a scored task corpus. Instead of relying on manual prompt iteration, it measures performance improvements, identifying the best working 'harness genome.' It is ideal for measuring sustainable improvements in task performance and supports a free, cost-estimating dry-run mode before committing to actual model calls.

This tool provides state-of-the-art semantic memory search across various knowledge domains. It supports multiple advanced retrieval strategies, including hybrid (sparse+dense) searching and Graph RAG for multi-hop reasoning. Key features include Mean Margin Ranking (MMR) for result diversity, recency weighting for timely information, and structured namespace filtering, ensuring highly relevant and context-aware results.

This tool assesses whether coding agents adhere to defined skills, rules, or agent definitions. It automatically generates scenarios with varying prompt strictness, executes the agent, and generates a comprehensive report detailing the compliance rate of tool calls against predefined workflow specifications using advanced LLM classification.