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.
Notes, actions and memory. Without a meeting bot. First month 100% off.
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Integrate web data into your AI product. One API to scrape website & brand data.
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belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
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Give your AI agent a complete email layer—sending, inbound inboxes, and sandbox testing.
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Notes, actions and memory. Without a meeting bot. First month 100% off.
Download for free →Show your product to 350K+ AI developers monthly.
(Empty days caused by temporary data issue)
Try for a month →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →Give your AI agent a complete email layer—sending, inbound inboxes, and sandbox testing.
Get 4K emails/month free →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →First SeenJun 11, 2026
