Ce Optimize
This is a structured experimentation framework for optimizing anything measurable through parallel trials and automatic convergence. You define a spec with a primary metric (either hard numbers like build time or LLM-as-judge scores for quality), set degenerate gates to filter out regressions, and it runs batches of experiments while keeping a crash-safe append-only log on disk. The discipline here is serious: every result gets written and verified immediately, not cached in conversation context, because these runs take hours and sessions die. Works well for tuning prompts, search relevance, clustering parameters, or build performance. Start conservative with serial mode and low iteration caps until your measurement harness is solid.
- skills.sh installs
- 3.4K
- GitHub stars
- 26K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add everyinc/compound-engineering-plugin --skill ce-optimize --agent claude-codeInstalls into .claude/skills of the current project.
Files
Optimize a measurable target
Outcome: confirmed improvements to the named target live on an optimize/<spec-name> branch, with a disk log. The user takes over at wrap-up.
Intent: the next action is the cheapest step that would change what gets implemented. Attribute the cost of a named workload before searching implementations. Search and keep a scored variant space without requiring a profile.
Done when: a stopping criterion was met, every declared required target is met or another stop was met first, the final state is written and verified on disk, and the user has been given the post-completion options. If the run instead stopped at a check it could not pass, say what blocked it.
Invoking this skill authorizes reading the repo, building the harness, and (after the Phase 1 approval gate) isolated experiments and keep/revert commits on optimize/<spec-name>. Ask when spend is uncapped, when a new dependency appears, when wrap-up would push or open a PR, or when only the user can choose among the post-completion options. Do not ask again to run the next experiment inside those limits.
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- Repository
- github.com/everyinc/compound-engineering-plugin
- Categories
- DevOps & CI/CD, Code Review & Quality, AI & Agent Building, Debugging
- First seen
- Jun 3, 2026
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