Compound Engineering
A reusable skill set that helps each AI-assisted engineering cycle leave better context for the next.
- Source repo
- EveryInc/compound-engineering-plugin
- Stars
- ★ 26k
- Last updated
- today
- License
- MIT
- Primary language
- TypeScript
- FA score
- 57/100 · Major gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex · Claude Code
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- A developer wants to turn an underspecified feature idea into a plan before asking a coding agent to implement it.
- Not a fit if
- Developers who only want a single coding assistant without planning, review, and learning capture
- Source review
- 57/100 · Major gaps
What does this agent do, and when should you use it?
Compound Engineering is a 36-skill plugin for AI coding agents, including Claude Code, Codex, and Cursor. Its workflow moves through brainstorming, planning, implementation, simplification, review, and learning capture, using each host's skill or command interface. The skills work with project code and plans, and can record durable learnings in the project's docs/solutions/ for later planning. Its lfg autonomous workflow can carry out the plan, review, and testing stages, then push, open a PR, and watch CI when a Git remote is available. It suits teams that want planning, review, and reusable project knowledge in their AI-assisted development process; installation and some behavior vary by host.
Run /ce-brainstorm in a project to use interactive Q&A to shape requirements and write a requirements plan; /ce-plan turns that plan into implementation steps. /ce-work executes the plan, /ce-simplify-code refines new code, /ce-code-review performs a report-only multi-agent review against the plan, and /ce-compound writes reusable learnings to docs/solutions/. Start with /ce-setup to report optional tool capabilities and create .compound-engineering/config.yaml. Starting /lfg after requirements are captured can chain implementation, simplification, review and fixes, learning capture, browser tests, and commits; with a remote it can also push, open a PR, and watch CI. Each host has its own installation and skill invocation method.
- A developer wants to turn an underspecified feature idea into a plan before asking a coding agent to implement it.
- A team wants code reviewed against the implementation plan before merge, with review changes applied only through the intended workflow.
- An engineering team repeatedly encounters project-specific pitfalls and wants to preserve solutions for future tasks.
- An individual developer wants to start an end-to-end implementation, testing, commit, and PR workflow from captured requirements.
- A team uses more than one coding host, such as Claude Code, Codex, or Cursor, and wants a shared engineering workflow.
How do you install or deploy this agent?
Choose the installation path for your coding host. Codex CLI requires registering the marketplace before installing the plugin; restart Codex afterward. Claude Code and Cursor can install through their plugin marketplaces. The README does not specify universal model-cost or account requirements; these depend on the host and model service.
codex plugin marketplace add EveryInc/compound-engineering-plugin
codex plugin add compound-engineering@compound-engineering-pluginHow do you use this agent?
In a project, start with /ce-setup, then use the core loop as needed. In Codex, invoke installed skills with a $ prefix; other slash-skill hosts use / examples. For the autonomous flow, start /lfg after brainstorming has captured the requirements.
/ce-setup
/ce-brainstorm make background job retries safer
/ce-plan
/ce-work
/ce-simplify-code
/ce-code-review
/ce-compoundCodex invocation examples:
$ce-plan
$lfgWhat are this agent's strengths and limitations?
- Its 36 skills cover requirements discovery, implementation planning, code simplification, review, and learning capture in one defined loop.
ce-compoundrecords learnings in project documentation that laterce-brainstormandce-planruns can use.- The README documents support across 14 hosts, including installation instructions for the native Codex plugin.
lfgcan connect implementation, review, browser testing, commits, and—when a remote exists—PR and CI follow-up.
- The plugin must be installed in a supported coding host, and install, reload, and invocation steps differ by host.
- Using the full workflow means adopting several stages and its planning and review practices.
lfgneeds a Git remote for push, PR, and CI follow-up; without one it stops at local commits.- The README does not specify model-call costs, data-handling details, or feature parity across every host, so those conditions need host-specific review.
How does this agent compare with similar options?
Compared with prompting a coding assistant to write code directly, the plugin adds requirements planning, plan-based review, and persistent learning capture. The README does not provide a feature-by-feature comparison with other plugins.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| Compound Engineering This agent | 57 · Major gaps | Agent plugin / skill | ★ 26k | today | TypeScript | Codex · Claude Code |
| CoCo Super Intelligence | 69 · Some gaps | Agent plugin / skillFree + model costs | ★ 826 | 2d ago | Python | Codex · Claude Code |
| Concord MCP | 67 · Some gaps | — | ★ 568 | today | TypeScript | Codex · Claude Code |
| OpenCodeReview | 53 · Major gaps | CLIFree + model costs | ★ 48k | today | Go | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
The README describes multi-host workflows and says /lfg can implement, simplify, review, commit, and, when a remote exists, push, open a PR, and watch CI. It says merging requires authorization, supporting external effects at 2. The docs also describe some install paths as self-contained, but provide no permission matrix, detailed data flows, sensitive-data handling rules, or general rollback path. A backup appears only in a plan code example and does not establish shipped behavior, so the other trust scores remain conservative. The README names two maintainers, but the object metadata says publisher identity is unverified, and no clear security update responsibility path is shown; source attribution scores 1.
The README gives install and refresh steps for major hosts and mentions cases such as no detected tools and an unparseable settings file, supporting dependency availability at 2 and failure messages at 1. The supplied plans have different dates and statuses, with some marked completed or superseded and others active; their relationship to the current README is not fully verifiable, so self-consistency scores 1. Plan claims about tests are not treated as execution or independent test evidence here.
The material explicitly covers many coding-agent hosts, a core workflow, on-demand skills, and varied installation scenarios, so audience and scenario coverage is thorough. It states boundaries for /lfg, including a bounded repair loop, the possibility of finishing with leftovers at the budget limit, and no merge without authorization; this supports capability boundaries and trigger precision at 2, while host-specific permission and compatibility differences are not comprehensively covered. Host-specific install paths and configuration guidance support environment fit at 3.
The README clearly organizes philosophy, workflow, skill catalog, installation, limitations, FAQ, development, and security/privacy entry points. Installation instructions list commands, refresh steps, and configuration details by host, so information architecture and install notes score 3. Naming is generally patterned, but the material mentions historical renames and legacy-install cleanup, so naming stability scores 2. Examples, FAQ, and limitations exist but are not exhaustive. MIT metadata and license documentation are explicit, scoring 3. The changelog points to release history without including it in the supplied material; maintainers are named and contribution paths exist, but maintenance responsibility and update path are not fully specified, so those scores are 2.
The skills connect brainstorming, planning, implementation, simplification, review, and knowledge capture into a reusable workflow, with directly callable examples; output usability and marginal value score 2. The material also indicates substantial planning and review steps and that /lfg can start a long automated workflow. It provides no cost, time, or outcome comparisons, so cost-benefit scores 1.
The README links skill purposes to guides and identifies SKILL.md as the runtime specification; plan material also names implementation files and acceptance conditions, supporting claim traceability at 2. Most supporting material comes from documents within the same repository, and plan claims about completion and tests lack independent corroboration, so cross-source corroboration scores 1. The README generally separates feature descriptions from usage examples, while plans record assumptions, unverified items, and completion status; this supports fact-inference separation at 2, with the limitation that this review can use only the supplied static excerpts.
- The documented /lfg flow can commit, push, open a PR, and monitor CI. Before use, check the authorization prompts and configuration of the selected host.
- The security, privacy, and individual skill runtime files are not included here. Do not treat README summaries or plan completion claims as independent verification of those behaviors.
FAQ
Can I use it with Codex?
Do I need Bun?
Does the review skill modify code automatically?
ce-code-review is report-only; the README says applying changes locally is explicit. The lfg workflow runs review and applies fixes.Will /lfg automatically merge or publish?
Do all skills require extra tools or the default documentation folders?
docs/solutions/ and docs/plans/ as defaults. The docs_root setting can relocate artifacts under another repository-relative root.