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ce-doc-review
Review requirements, plans, or specs with role-specific lenses. Use when the user wants to improve an existing planning document.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Review requirements, plans, or specs with role-specific lenses. Use when the user wants to improve an existing planning document.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Run browser tests for pages affected by the current branch or PR.
Babysits or watches an open GitHub PR until merge-ready, continuously reacting to new review comments and CI failures throughout the PR's life. Use when asked to 'babysit the PR', 'watch the PR', monitor, or keep an eye on a PR over time — not a one-shot request to resolve review comments or debug one CI failure (those are separate skills). GitHub only, including GitHub Enterprise.
Commit, push, and open a PR. Use when asked to ship/open a PR, or for PR-description-only flows like writing, rewriting, or describing a PR body.
Diagnosis loop for bugs and failing behavior. Use for errors, stack traces, regressions, failed tests, issue-tracker bugs, stuck investigations after failed fixes, or asks to debug/fix a bug.
Resolve PR review feedback. Use when addressing review comments, resolving review threads, or fixing code-review feedback.
Check Compound Engineering health and repo-local config.
| name | ce-doc-review |
| description | Review requirements, plans, or specs with role-specific lenses. Use when the user wants to improve an existing planning document. |
| argument-hint | [mode:headless] [path/to/document.md] |
Review requirements or plan documents through multi-persona analysis. Dispatches generic subagents seeded with skill-local reviewer prompt assets, auto-applies safe_auto fixes, and routes remaining findings through a four-option interaction (per-finding walk-through, auto-resolve with best judgment, Append-to-Open-Questions, Report-only) for user decision.
AskUserQuestion is a deferred tool — its schema is not available at session start. At the start of Interactive-mode work (before the routing question, per-finding walk-through questions, bulk-preview Proceed/Cancel, and Phase 5 terminal question), call ToolSearch with query select:AskUserQuestion to load the schema. Load it once, eagerly, at the top of the Interactive flow — do not wait for the first question site. On Codex, Gemini, and Pi this preload is not required.ToolSearch returns no match, the tool call explicitly fails, or the runtime mode does not expose it (e.g., Codex edit modes where request_user_input is unavailable). A pending schema load is not a fallback trigger; call ToolSearch first per the pre-load rule. In genuine-fallback cases, present options as a numbered list and wait for the user's reply — never silently skip the question. Rendering a question as narrative text because the tool feels inconvenient, because the model is in report-formatting mode, or because the instruction was buried in a long skill is a bug. A question that calls for a user decision must either fire the tool or fall back loudly.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. ce-doc-review still applies the same judgment about which tier each finding belongs in. The only difference is how non-safe_auto findings are delivered:
safe_auto fixes are applied silently (same as interactive)gated_auto, manual, and FYI findings are returned as structured text for the caller to handle — no blocking-question prompts, no interactive routingThe 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("ce-doc-review", "mode:headless docs/plans/my-plan.md")
If mode:headless is not present, the skill runs in its default interactive mode with the routing question, walk-through, and bulk-preview behaviors documented in references/walkthrough.md and references/bulk-preview.md.
If a document path is provided: Read it, then proceed. If the Read fails or the file is not on disk, apply the missing-document gate below instead of continuing.
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("ce-doc-review", "mode:headless ")" without dispatching agents.
Missing-document gate — verify before any dispatch. Persona reviewers read documents from the filesystem, and several run without Bash, so they cannot read git refs — a path that exists only on a branch that is not checked out wastes the entire persona team discovering they cannot proceed (issue #925). Before Phase 2, confirm every resolved document path is readable on disk (the Read above succeeded). Location does not matter: an absolute path outside the checkout (e.g. /tmp/plan.md) or a doc in another checkout reviews fine. If any path is not readable, do not dispatch any personas:
Classify the document by reading its content shape, not its file path. Path is a tie-breaker hint, not the primary signal — a brainstorm-style doc placed under docs/plans/ should still classify as requirements, and a plan-shaped doc under docs/brainstorms/ should still classify as plan. The reviewers below operate differently depending on this classification, so misclassifying a plan-shaped doc as a requirements doc (or vice versa) produces noisy or under-scrutinized findings.
First check for the unified artifact contract:
artifact_contract: ce-unified-plan/v1 plus artifact_readiness: requirements-only -> classify as unified-requirements. Review the Product Contract only; the absence of Planning Contract, Implementation Units, Verification Contract, or Definition of Done is expected and must not be flagged.artifact_contract: ce-unified-plan/v1 plus artifact_readiness: implementation-ready -> classify as unified-plan. Review Product Contract and Planning Contract with different lenses, then review Implementation Units/Verification/DoD for execution completeness..html) are read/reviewed in report-only mode. Do not apply markdown mutation paths to HTML. If a caller requested mutation/autofix behavior, skip with the existing markdown-only message or return report-only findings.active, in_progress, completed, done) are a document-contract finding, not an execution state to honor.Use these signals to decide:
requirements signals (what-to-build documents):
actors:, flows:, acceptance_examples:, or status: carrying brainstorm-shaped valuesAcceptance Examples, Actors, Key Flows, User Flows, Outstanding Questions, Resolve Before PlanningR1, R2, A1, F1, AE1 — requirement, actor, flow, and acceptance-example IDsplan signals (how-to-build documents):
type: feat|fix|refactor, origin: docs/brainstorms/..., or product_contract_source: ce-brainstorm|ce-plan-bootstrap|legacy-requirementsImplementation Units, Output Structure, Key Technical Decisions, Risks & Dependencies, System-Wide ImpactU1, U2 — implementation unit IDsGoal, Files, Approach, Test scenarios, VerificationTie-breaker rule. When the content signals are mixed or sparse, fall back to path: legacy docs/brainstorms/ → requirements, docs/plans/ → plan unless unified metadata says otherwise. When neither path location applies, treat the dominant content shape as authoritative; if shape is genuinely ambiguous, default to requirements (the more conservative classification — it activates fewer plan-specific feasibility checks).
Pass the classification result to each persona via the {document_type} slot in the subagent template. Personas read this and adapt their analysis accordingly.
Analyze 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 a high-value challenge surface, not merely structural complexity. Routine plans with stated rationale are not by themselves an adversarial signal — premise/assumption work re-litigates settled questions when the only signal is "this plan is well-structured." Activate when ANY of the following holds:
origin: requirements doc and no product_contract_source: ce-brainstorm or legacy-requirements) -- premise wasn't validated upstreamDo NOT activate adversarial on a routine plan document that derives from a validated upstream Product Contract, stays within scope, and does not introduce high-stakes domains or new abstractions. Validated upstream provenance includes legacy origin: docs/brainstorms/..., product_contract_source: ce-brainstorm, and product_contract_source: legacy-requirements. A direct product_contract_source: ce-plan-bootstrap plan is greenfield and does not suppress premise-level techniques by itself. The plan's structural decisions (more units, more rationale) are not by themselves adversarial signal -- those are the plan doing its job.
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:
coherence-reviewerfeasibility-reviewerAdd activated conditional personas:
product-lens-reviewerdesign-lens-reviewersecurity-lens-reviewerscope-guardian-revieweradversarial-document-reviewerDispatch generic subagents using bounded parallelism with the platform's subagent primitive (e.g., Agent in Claude Code, spawn_agent in Codex) where available; otherwise run the work inline or serially. Omit the mode parameter so the user's configured permission settings apply. Respect the current harness's active-subagent limit: queue selected reviewers, dispatch only as many as the harness accepts, and fill freed slots as reviewers complete. Treat active-agent/thread/concurrency-limit spawn errors as backpressure, not reviewer failure: leave the reviewer queued and retry after a slot frees. Record a reviewer as failed only after a successful dispatch times out/fails, or when dispatch fails for a non-capacity reason.
For each selected reviewer, read the matching skill-local prompt asset at references/personas/<reviewer-name>.md and pass its full content as {persona_file}. Do not dispatch standalone agents by type/name and do not rely on platform-level custom-agent registration.
Model tiering lives here, not in prompt assets. Local prompt files have no frontmatter and carry no model metadata. Apply these dispatch-time preferences when the platform exposes a known model override; otherwise omit the override and inherit the parent model rather than guessing a platform-specific model name:
coherence-reviewer: cheapest capable extraction/reasoning tier.design-lens-reviewer, scope-guardian-reviewer: platform mid-tier model.security-lens-reviewer, feasibility-reviewer, product-lens-reviewer, adversarial-document-reviewer: inherit the parent model unless the harness has an established high-capability review tier.Each subagent receives the prompt built from the subagent template included below with these variables filled:
| Variable | Value |
|---|---|
{persona_file} | Full content of the selected local prompt asset from references/personas/ |
{schema} | Content of the findings schema included below |
{document_type} | "requirements", "plan", "unified-requirements", or "unified-plan" from Phase 1 classification |
{document_path} | Path to the document |
{origin_path} | Upstream Product Contract provenance extracted once during Phase 1: prefer the document's origin: frontmatter field when present; otherwise use product_contract_source:<value> when present; otherwise use none. Personas that adapt on origin/provenance (product-lens, adversarial, scope-guardian) read this slot to gate technique suppression — they do NOT re-parse frontmatter themselves. |
{document_content} | Reviewer-specific section slice. For unified artifacts, pass metadata, Goal Capsule, and only the relevant slice: product-lens/adversarial/scope reviewers get Product Contract; feasibility/coherence reviewers also get Planning Contract and active Implementation Units/Verification/DoD when artifact_readiness: implementation-ready. For legacy documents, pass the full document. |
{decision_primer} | Cumulative prior-round decisions in the current session, or an empty <prior-decisions> block on round 1. See "Decision primer" below. |
For legacy requirements/plan documents, pass each subagent the full
document — do not split into sections. For unified artifacts, do not pass the
full artifact to every reviewer by default: unified plans can be large, so
section slices (per the {document_content} slot above) are the default.
Escalate to a broader slice only when the reviewer needs cross-section
traceability that the initial slice cannot assess.
On round 1 (no prior decisions), set {decision_primer} to:
<prior-decisions>
Round 1 — no prior decisions.
</prior-decisions>
On round 2+ (after one or more prior rounds in the current interactive session), accumulate prior-round decisions and render them as:
<prior-decisions>
Round 1 — applied (N entries):
- {section}: "{title}" ({reviewer}, {confidence})
Evidence: "{evidence_snippet}"
Round 1 — rejected (M entries):
- {section}: "{title}" — Skipped because {reason}
Evidence: "{evidence_snippet}"
- {section}: "{title}" — Deferred to Open Questions because {reason or "no reason provided"}
Evidence: "{evidence_snippet}"
- {section}: "{title}" — Acknowledged without applying because {reason or "no suggested_fix — user acknowledged"}
Evidence: "{evidence_snippet}"
Round 2 — applied (N entries):
...
</prior-decisions>
Each entry carries an Evidence: line because synthesis R29 (rejected-finding suppression) and R30 (fix-landed verification) both use an evidence-substring overlap check as part of their matching predicate — without the evidence snippet in the primer, the orchestrator cannot compute the >50% overlap test and has to fall back to fingerprint-only matching, which either re-surfaces rejected findings or suppresses too aggressively. The {evidence_snippet} is the first evidence quote from the finding, truncated to the first ~120 characters (preserving whole words at the boundary) and with internal quotes escaped. If a finding has multiple evidence entries, use the first one; the rest live in the run artifact and are not needed for the overlap check.
Accumulate across all rounds in the current session. Skip, Defer, and Acknowledge actions all count as "rejected" for suppression purposes — each signals the user decided the finding wasn't worth actioning this round (Acknowledge is the no-fix-guard variant: the user saw a finding with no suggested_fix, chose not to defer or skip explicitly, and recorded acknowledgement instead; for round-to-round suppression that is semantically equivalent to Skip). Applied findings stay on the applied list so round-N+1 personas can verify fixes landed (see R30 in references/synthesis-and-presentation.md).
Cross-session persistence is out of scope. A new invocation of ce-doc-review on the same document starts with a fresh round 1 and no carried primer, even if prior sessions deferred findings into the document's Open Questions section.
Error handling: If a subagent fails or times out, proceed with findings from subagents that completed. Note the failed reviewer in the Coverage section. Do not block the entire review on a single reviewer failure.
Dispatch limit: Even at maximum (7 agents), use bounded parallel dispatch. If the harness cap is lower than the selected team size, queue the remainder and launch them as active reviewers complete.
After all dispatched agents return, read references/synthesis-and-presentation.md for the synthesis pipeline (validate, anchor-based gate, dedup, cross-persona agreement promotion, resolve contradictions, auto-promotion, route by three tiers with FYI subsection), safe_auto fix application, headless-envelope output, and the handoff to the routing question.
For the four-option routing question and per-finding walk-through (interactive mode), read references/walkthrough.md. For the bulk-action preview used by best-judgment routing, Append-to-Open-Questions, and walk-through Auto-resolve with best judgment on the rest, read references/bulk-preview.md. Do not load these files before agent dispatch completes.
@./references/subagent-template.md
@./references/findings-schema.json
Selected reviewer prompt assets live under references/personas/. Read only the prompt files selected for the current review.