# Optimize

Drive structured autoresearch iteration after evo:discover and the baseline commit.

- Repository: https://github.com/evo-hq/evo (1491 stars)
- Category: Git and review
- License: Apache-2.0
- Last updated: 2026-10-05
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add evo-hq/evo --skill optimize -g -a claude-code -y`
Codex: `npx skills add evo-hq/evo --skill optimize -g -a codex -y`
Cursor: `npx skills add evo-hq/evo --skill optimize -g -a cursor -y`
Gemini CLI: `npx skills add evo-hq/evo --skill optimize -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add evo-hq/evo`

## Description

Drive structured autoresearch iteration after evo:discover and the baseline commit. Use when the user invokes /evo:optimize or asks to try ideas, try variants, run experiments, use available GPUs, improve the current best/frontier, continue an evo search, or compare candidate changes in an evo workspace. The orchestrator plans and spawns optimization subagents; candidate edits/runs belong to those subagents. Width is set via subagents=N (1 for serial workloads, larger for parallel); the loop's structural value applies at any width.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

Run the `evo` optimization loop. Each round, the orchestrator writes structured briefs and spawns subagents that execute within them. Each subagent is semi-autonomous: it reads the pointer traces, forms the concrete edit, runs experiments, and can iterate within its branch. Runs until interrupted or the stall limit is reached.

**This skill is the canonical loop for ALL post-discover work, including serial workloads.** If the workspace's resource profile forces width 1 (single GPU, single-process benchmark, etc.), you still invoke `/evo:optimize` -- just pass `subagents=1`. The loop's value is the STRUCTURE around each experiment (scan-subagent cross-cutting analysis between rounds, verifier pre/post hooks via the subagent skill, ideator spawning on stall, frontier reconciliation, stop-hook discipline), NOT just parallelism. Bypassing optimize because "I'm running serial work anyway" loses every piece of that structure -- you've reverted to ad-hoc experiment iteration with none of evo's loop benefits, just the bookkeeping.

**Plain-language trigger.** In an initialized evo workspace, casual user wording
like "try a couple ideas", "try different variants", "use the available GPUs",
"continue from the current best", or "see what improves" is an optimize request
unless the user explicitly asks for a read-only report. Do not treat the lack of
a slash command as permission to bypass this protocol. Loading this skill from
plain-language wording is also explicit authorization to use the host's
subagent mechanism for the resolved round width; the user does not have to say
"spawn subagents" or "parallel agents" separately.

The rest: https://github.com/evo-hq/evo/blob/HEAD/plugins/evo/npm/skills/optimize/SKILL.md