Review requirements or plan documents through multi-persona analysis. Dispatches specialized reviewer agents in parallel, auto-fixes quality issues, and presents strategic questions for user decision.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondocument-reviewExecute the skills CLI command in your project's root directory to begin installation:
Fetches document-review from everyinc/compound-engineering-plugin and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate document-review. Access via /document-review in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Review requirements or plan documents through multi-persona analysis. Dispatches specialized reviewer agents in parallel, auto-fixes quality issues, and presents strategic questions for user decision.
Check the skill arguments for mode:headless. Arguments may contain a document path, mode:headless, or both. Tokens starting with mode: are flags, not file paths -- strip them from the arguments and use the remaining token (if any) as the document path for Phase 1.
If mode:headless is present, set headless mode for the rest of the workflow.
Headless mode changes the interaction model, not the classification boundaries. Document-review still applies the same judgment about what has one clear correct fix vs. what needs user judgment. The only difference is how non-auto findings are delivered:
auto fixes are applied silently (same as interactive)present findings are returned as structured text for the caller to handle -- no AskUserQuestion prompts, no interactive approvalThe caller receives findings with their original classifications intact and decides what to do with them.
Callers invoke headless mode by including mode:headless in the skill arguments, e.g.:
Skill("compound-engineering:document-review", "mode:headless docs/plans/my-plan.md")
If mode:headless is not present, the skill runs in its default interactive mode with no behavior change.
If a document path is provided: Read it, then proceed.
If no document is specified (interactive mode): Ask which document to review, or find the most recent in docs/brainstorms/ or docs/plans/ using a file-search/glob tool (e.g., Glob in Claude Code).
If no document is specified (headless mode): Output "Review failed: headless mode requires a document path. Re-invoke with: Skill("compound-engineering:document-review", "mode:headless ")" without dispatching agents.
After reading, classify the document:
docs/brainstorms/, focuses on what to build and whydocs/plans/, focuses on how to build it with implementation detailsAnalyze the document content to determine which conditional personas to activate. Check for these signals:
product-lens -- activate when the document makes challengeable claims about what to build and why, or when the proposed work carries strategic weight beyond the immediate problem. The system's users may be end users, developers, operators, maintainers, or any other audience -- the criteria are domain-agnostic. Check for either leg:
Leg 1 — Premise claims: The document stakes a position on what to build or why that a knowledgeable stakeholder could reasonably challenge -- not merely describing a task or restating known requirements:
Leg 2 — Strategic weight: The proposed work could affect system trajectory, user perception, or competitive positioning, even if the premise is sound:
design-lens -- activate when the document contains:
security-lens -- activate when the document contains:
scope-guardian -- activate when the document contains:
adversarial -- activate when the document contains:
Tell the user which personas will review and why. For conditional personas, include the justification:
Reviewing with:
- coherence-reviewer (always-on)
- feasibility-reviewer (always-on)
- scope-guardian-reviewer -- plan has 12 requirements across 3 priority levels
- security-lens-reviewer -- plan adds API endpoints with auth flow
Always include:
compound-engineering:document-review:coherence-reviewercompound-engineering:document-review:feasibility-reviewerAdd activated conditional personas:
compound-engineering:document-review:product-lens-reviewercompound-engineering:document-review:design-lens-reviewercompound-engineering:document-review:security-lens-reviewercompound-engineering:document-review:scope-guardian-reviewercompound-engineering:document-review:adversarial-document-reviewerDispatch all agents in parallel using the platform's task/agent tool (e.g., Agent tool in Claude Code, spawn in Codex). Omit the mode parameter so the user's configured permission settings apply. Each agent receives the prompt built from the subagent template included below with these variables filled:
| Variable | Value |
|---|---|
{persona_file} |
Full content of the agent's markdown file |
{schema} |
Content of the findings schema included below |
{document_type} |
"requirements" or "plan" from Phase 1 classification |
{document_path} |
Path to the document |
{document_content} |
Full text of the document |
Pass each agent the full document -- do not split into sections.
Error handling: If an agent fails or times out, proceed with findings from agents that completed. Note the failed agent in the Coverage section. Do not block the entire review on a single agent failure.
Dispatch limit: Even at maximum (7 agents), use parallel dispatch. These are document reviewers with bounded scope reading a single document -- parallel is safe and fast.
After all dispatched agents return, read references/synthesis-and-presentation.md for the synthesis pipeline (validate, gate, dedup, promote, resolve contradictions, route by autofix class), auto-fix application, finding presentation, and next-action menu. Do not load this file before agent dispatch completes.
@./references/subagent-template.md
@./references/findings-schema.json
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Solid pick for teams standardizing on skills: document-review is focused, and the summary matches what you get after install.
We added document-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
document-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
document-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
document-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
document-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added document-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: document-review is focused, and the summary matches what you get after install.
Registry listing for document-review matched our evaluation — installs cleanly and behaves as described in the markdown.
Registry listing for document-review matched our evaluation — installs cleanly and behaves as described in the markdown.
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