Compound Engineering is a plugin that organizes software work into brainstorming, planning, implementation, review, and recording lessons for future changes. It is used with AI coding agents including Claude Code, Cursor, and Codex, and the catalogue entries provide parts of its agent, skill, command, and hook workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add EveryInc/compound-engineering-plugin --skill ce-optimizegit clone --depth 1 https://github.com/EveryInc/compound-engineering-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/everyinc/compound-engineering-plugin/ce-optimize)<a href="https://agentmods.dev/skills/everyinc/compound-engineering-plugin/ce-optimize"><img src="https://agentmods.dev/badge/skills/everyinc/compound-engineering-plugin/ce-optimize/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/everyinc/compound-engineering-plugin/ce-optimize"><img src="https://agentmods.dev/badge/skills/everyinc/compound-engineering-plugin/ce-optimize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.01718 |
| Opus 5.5 | $0.00025 | $0.00687 |
| Sonnet 5.5 | $0.00013 | $0.00344 |
| Haiku 4.5 | $0.00006 | $0.00172 |
Grade A, and why
ce-optimize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
Independent calls and dispatches go in one response; serialize only real dependencies.
Report findings, user decisions, blockers, and results. During longer work, give occasional updates on what was learned and what remains. Routine preparation and phase or batch transitions need no announcement. Keep accounting in the log and final recap unless it affects a current decision.
Explain the target, evidence, and decision in ordinary task language. Workflow labels (such as 'harness') belong in artifacts unless the user asks about those mechanics. State unknown duration or cost as unknown; caps are limits, not forecasts.
A step is done only after it ran. Describing a measurement, dispatch, or checkpoint is not doing it. Do not end a turn while in-scope work remains merely described. Outstanding work may outlive the turn only with a verified checkpoint and either bounded automatic resumption or an explicit manual-resume handback, as references/persistence.md defines.
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/agents/learnings-researcher.md 16 KB
- references/agents/repo-research-analyst.md 15 KB
- references/example-expensive-benchmark-spec.yaml 2.1 KB
- references/example-hard-spec.yaml 1.3 KB
- references/example-judge-spec.yaml 2.2 KB
- references/example-text-target-spec.yaml 2.9 KB
- references/experiment-log-schema.yaml 24 KB
- references/experiment-prompt-template.md 8.6 KB
- references/judge-prompt-template.md 6.7 KB
- references/loop.md 38 KB
- references/measurement.md 18 KB
- references/optimize-spec-schema.yaml 27 KB
- references/persistence.md 11 KB
- references/spec.md 10 KB
- references/text-targets.md 6.7 KB
- references/usage-guide.md 6.1 KB
- references/wrap-up.md 7.2 KB
- scripts/decide.mjs 22 KB runs code
- scripts/experiment-worktree.sh 10 KB runs code
- scripts/measure.sh 3.9 KB runs code
- scripts/parallel-probe.sh 5.0 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +2 lines d44b1723df39
- 26d ago Changed 942ff8ce14c4
- 1mo ago Changed d8e18a7f4772
- 1mo ago Changed 771d822cab9c
- 1mo ago Changed · +9 lines · +44 tokens per session fb0bb36a9a98
- 1mo ago First seen · 54 lines · 19 tokens per session scan A e4733c2cec3b
ce-optimize is a skill published in the GitHub repository EveryInc/compound-engineering-plugin (25,727 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 1,718 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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