Summary
After you've run discover and committed your baseline, this is the loop that drives all subsequent optimization work. It orchestrates rounds of structured experimentation: spawns subagents with concrete briefs, runs cross-cutting analysis between rounds, dispatches ideator subagents on stall, enforces verifier hooks pre and post. The width argument (subagents=N) scales from 1 for serial workloads up to whatever your binding resource allows, but the real value is the structure itself. Frontier-based parent selection, annotation discipline, and the scan-subagent cycle apply whether you're running one experiment at a time on a single GPU or fanning out across cores. Don't skip it just because your benchmark forces serial execution. You'd lose the scaffolding that makes evo autoresearch instead of ad-hoc iteration.
Install to Claude Code
npx -y skills add evo-hq/evo --skill optimize --agent claude-codeInstalls into .claude/skills of the current project.
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Connect Claude to +800M contacts, +150M companies. Find & Enrich leads in chat.
Try For Free →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →An agent that runs the SEO playbooks that move rankings and ships PRs you control.
Get founding access →First SeenJun 11, 2026
