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Turn your codebase into an automated research loop for benchmark-driven optimization.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "evo" yet — see the docs or source repo.
Analyze this codebase, identify the most important performance and quality metrics, automatically instrument benchmark tests, and propose one round of search-based optimization experiments.
A set of recommended metrics, benchmark design, instrumentation approach, and a first-round optimization experiment plan.
For this project’s build speed and test pass rate, launch parallel subagents to search different improvement paths, compare results, and summarize the best direction.
A comparison of multiple candidate improvements with a recommended implementation order and rationale.
After reviewing the repository structure, tests, and core modules, determine the most important evaluation metrics for this project and explain why they should be tracked continuously.
A prioritized list of core metrics tied to the project, with the engineering or business significance of each.
Build auditable self-evolving workflows and iteration systems for AI agents.
Automate JavaScript reverse engineering and deobfuscation with iterative workflow optimization.
Find surveys, papers, benchmarks, and open-source resources on self-evolving agents.
Run development tasks autonomously in batches while you are away.
Optimize coding agents with performance, security, memory, and research-first workflows.
Improve code and product names step by step through a three-phase process.