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Review spec-forge generated documents (SRS + tech-design + feature specs) for quality, completeness, and internal consistency. Finds issues like incomplete sections, contradictions, missing traceability, and vague specs, then optionally auto-fixes them. Supports iterative review-fix cycles that run until the review converges — passing, or a round with no net reduction in findings — typically 1–2 rounds.

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  • Added May 26, 2026
code-qualitypythongobashtestinggitapidocumentation

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  • api

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A100/100

Scanned September 23, 2026

npx -y skills add tercel/spec-forge --skill review --agent claude-code

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SKILL.md
---
name: review
description: >
  Review spec-forge generated documents (SRS + tech-design + feature specs) for quality, completeness,
  and internal consistency. Finds issues like incomplete sections, contradictions, missing
  traceability, and vague specs, then optionally auto-fixes them. Supports iterative
  review-fix cycles that run until the review converges — passing, or a round with no
  net reduction in findings — typically 1–2 rounds.
instructions: >
  Follow the workflow below exactly. This skill reviews specification documents generated by
  spec-forge (SRS, tech-design, feature specs, overview). It does NOT review code or non-spec documents.
  Every finding must cite a specific file and section. Do NOT fabricate issues — only report what
  you actually find. Auto-fix only modifies cited sections, never restructures entire documents.
---

# Review — Specification Quality & Consistency Review

Systematically review spec-forge generated documents for quality, completeness, and internal consistency. Optionally auto-fix issues found.

## Core Principles

1. **Evidence-based**: Every finding must cite a specific file and section — no vague complaints
2. **Spec-focused**: Review specification documents only (SRS, tech-design, feature specs, overview) — not code, not upstream idea drafts
3. **Upstream-aware**: Use idea drafts and project manifests as reference context to validate spec accuracy, but do not review them
4. **Prioritized**: Findings classified by severity so the user can act on what matters first
5. **Conservative fixes**: Auto-fix only touches cited sections; when domain knowledge is missing, leave a `<!-- REVIEW: {question} -->` comment instead of guessing
6. **Honest**: Report real issues, don't inflate findings to look thorough

## Severity Levels

| Severity | Meaning | Example |
|----------|---------|---------|
| **Critical** | Wrong, contradictory, or misleading content | Feature spec API signature contradicts tech-design, component boundary mismatch |
| **Major** | Significant gap that would block or confuse implementation | Empty required section, missing error handling spec, undefined edge cases |
| **Minor** | Quality issue that degrades usefulness but isn't blocking | Vague description, missing cross-reference, inconsistent terminology |

## Workflow

### Step 1: Determine Review Scope

Parse the arguments to determine what to review:

1. If a `feature_name` argument is provided, look for:
   - `docs/{feature_name}/srs.md` — **the delivery contract; review it first**, since a defect here propagates into every downstream document
   - `docs/{feature_name}/tech-design.md`
   - All feature specs in `docs/features/` (glob for `docs/features/*.md`)
   - Upstream reference: `docs/{feature_name}/prd.md` and `ideas/{feature_name}/draft.md` (if they exist)
   - Project manifest: `docs/project-{feature_name}.md` (if exists, for multi-split context)
2. If no argument, scan `docs/` for the most recent SRS and tech-design, plus all feature specs in `docs/features/`
3. If no spec documents found, inform the user and stop

Use `AskUserQuestion` to ask:
- **Review scope**: Review all generated specs, or focus on specific documents? (Options: All / SRS only / Tech design only / Feature specs only / Specific files)
- **Auto-fix**: Should I auto-fix issues found? (Options: Yes — fix Critical+Major automatically / Yes — fix all / No — report only)

### Step 2: Document Inventory

Build the list of documents to review:

1. **Review targets** (will be reviewed):
   - `docs/{feature_name}/srs.md`
   - `docs/{feature_name}/tech-design.md`
   - `docs/features/overview.md`
   - `docs/features/{component-1}.md`, `docs/features/{component-2}.md`, etc.
   - For multi-split: tech-designs for all sub-features

2. **Reference context** (read for context, NOT reviewed):
   - `docs/{feature_name}/prd.md` — upstream business case and capability priorities
   - `ideas/{feature_name}/draft.md` — upstream demand validation
   - `docs/project-{feature_name}.md` — project manifest with sub-feature scope

3. Read each review target document fully

Display the inventory:

```
Review scope: {feature_name}
  Review targets: {N} documents
    - docs/{feature_name}/tech-design.md
    - docs/features/overview.md
    - docs/features/{component-1}.md
    - docs/features/{component-2}.md
    ...
  Reference context: {N} documents
    - ideas/{feature_name}/draft.md
```

### Step 3: Review

Check each review target document against the following checklist:

#### 3.1 Completeness

**Fast path (preferred):** resolve `<sf_scripts>` (see `@../shared/scripts.md`) and run the structural gate per document —

```bash
python3 "<sf_scripts>/sf-verify-doc.py" "<file>" --strict
```

for each review target. This deterministically confirms the document is non-empty and titled, has the recommended sections for its type, has well-formed/unique IDs, and carries no leftover template placeholders or `{placeholder}` variables; use its findings as the completeness result and fix everything it flags. The script does structure, IDs, and placeholders — you still do the semantic checks (§3.3 specificity, API-signature-matching in §3.2). **Fallback:** if `python3` is unavailable or the script is not found, check by hand:
- Any empty sections, TBD/TODO markers, placeholder text, or `{placeholder}` template variables?
- Missing required sections per document type?
  - SRS: Introduction, Scope Boundaries, Overall Description, Functional Requirements, State Machines, Permission Matrix, Error Catalogue, Non-Functional Requirements, Data Requirements, External Interfaces, Traceability Matrix, Acceptance and Change Control
  - Tech design: Goals, Non-goals, Scope, Architecture, API Design, Data Model, Component Overview
  - Feature spec: Purpose, API/Interface, Logic/Behavior, Error Handling, Dependencies
  - Overview: Feature index listing all generated specs, dependency graph

#### 3.1a SRS Contract Integrity

The SRS is the delivery contract — what an implementation team is held to and what acceptance is settled against. A gap here is not a documentation blemish; it is an unsettleable dispute waiting to happen, and it propagates into every downstream document. Review it first and apply these checks in addition to §3.1:

- **Out-of-scope table populated** (§3.2). An empty table is a **Major** finding: it does not mean nothing is excluded, it means the exclusions are unwritten, and unwritten exclusions get built or get disputed. "Nothing is excluded" stated explicitly with a justification passes.
- **Input field rules present and exact.** Every requirement that accepts input has the table, and every rule states an exact value rather than a category — "reasonable length", "a valid value", "an appropriate size" are **Major** findings. Every rejection behavior names a code that exists in the Error Catalogue.
- **State machines complete.** Every entity with a lifecycle has both the legal-transition table *and* the illegal-transition handling table. A state machine with only legal transitions is **Major** — the implementer will invent the rest and acceptance testing will discover it.
- **Permission matrix with denial behavior.** Roles × operations × data scope, scopes defined as concrete predicates, and the 403-vs-404 decision stated. A matrix that omits the denial behavior is **Minor**; one that omits data scope is **Major**, since "can read" without a scope is ambiguous about whose records.
- **No generic error entries.** `INTERNAL_ERROR` or "operation failed" standing in for an anticipated condition is **Major**. Each distinct cause needs its own diagnosable code.
- **Degradation specified per dependency.** For each external dependency, the behavior when it is unavailable is stated. Missing degradation behavior is **Major** — it is the failure mode that reaches production untested.
- **Acceptance criteria objectively settleable.** A criterion whose pass/fail depends on reviewer judgement ("the interface should feel responsive") is **Major**: it is a defect in the specification, not a matter to resolve at acceptance time.
- **NFRs carry a verification method.** A target with no agreed way to measure it cannot be accepted or disputed. Missing verification method is **Major**.
- **Requirement ID stability.** If a prior version of this SRS exists in git history, confirm no issued `FR-*`/`NFR-*` ID was silently renumbered or repurposed. A renumbered ID is **Critical** — it severs every downstream reference, including any code-forge plan already generated from it.

#### 3.2 Internal Consistency
- **Requirement coverage**: every `FR-*`/`NFR-*` in the SRS is satisfied by at least one tech-design component, and every component names the requirements it satisfies. An unplaced requirement is **Major** — it is either a design gap or a requirement that should be renegotiated, and both need to be visible rather than silently dropped. Use `sf-trace.py matrix --upstream "<srs.md>" --downstream "<tech-design.md>"` for the coverage math, then judge whether each gap is intentional.
- **Scope boundaries carried through**: the tech-design's §3.4 Scope reflects the SRS's §3.2 out-of-scope table. An exclusion that disappears between the requirements and the design is **Major** — that is how out-of-scope work gets built.
- **Error catalogue realized**: every SRS error code maps to handling in the tech-design or a feature spec. An error code the design cannot produce is **Major**.
- **Component name matching**: verify the feature-spec files and the tech-design's §8.1 Component Overview describe the same component set.

  **Fast path (preferred):** resolve `<sf_scripts>` (see `@../shared/scripts.md`) and run the membership check —

  ```bash
  python3 "<sf_scripts>/sf-trace.py" chain --tech-design "<tech-design.md>" --features-dir "docs/features" --overview "docs/features/overview.md"
  ```

  Read its fields: `slugs_without_feature_file` (a §8.1 component with no matching feature spec), `features_not_mentioned_in_tech_design` (a feature spec with no matching component), and `overview_missing_features` (used in §3.4). **Fallback:** if `python3` is unavailable or the script is not found, compare the `docs/features/{name}.md` slugs against the §8.1 rows by hand.

  The script detects the mismatch; **you classify the severity** by whether it would actually break a downstream consumer like code-forge — do not hardcode Critical. A feature spec deliberately written ahead of the tech-design during iterative authoring is a Minor issue, not Critical; a genuine slug divergence that severs the traceability chain a consumer depends on is Critical.
- Do feature spec API signatures match the tech-design's API Design section?
- Do component boundaries in feature specs align with tech-design's Component Overview?
- Are data models consistent across documents? (field names, types, relationships)
- Do feature specs reference the same architectural patterns described in the tech-design?
- For multi-split: are cross-sub-feature interfaces consistent?

#### 3.3 Specificity
- Vague descriptions that should be concrete (e.g., "handles errors appropriately" → specific error codes/behaviors)
- Ambiguous quantifiers (e.g., "fast", "large", "many" without concrete thresholds)
- Undefined behavior for edge cases or boundary conditions

#### 3.4 Traceability
- Do feature specs reference back to tech-design sections they implement?
- Does overview.md list ALL generated feature specs? (no missing entries) — the `sf-trace.py chain` run in §3.2 reports this as `overview_missing_features` (feature specs absent from `overview.md`); fall back to scanning the feature index by hand if the script is unavailable.
- Are dependency relationships between feature specs documented and consistent?

#### 3.5 Actionability
- Could a developer implement from these specs without guessing?
- Are input/output formats fully specified?
- Are error scenarios and recovery behaviors defined?
- Are configuration options and defaults documented?

### Step 4: Generate Findings

For each issue found, produce a structured finding:

```
- [{severity}] {file_path} § {section}: {description of issue} → FIX: {concrete fix instruction}
```

Compile the full review result:

```
REVIEW_RESULT: {PASS | ISSUES_FOUND}
CRITICAL_COUNT: {N}
MAJOR_COUNT: {N}
MINOR_COUNT: {N}

FINDINGS:
- [{severity}] {file_path} § {section}: {description} → FIX: {fix instruction}
...
```

### Step 5: Present Results

Display summary:

```
spec-forge review: {feature_name}

  Documents reviewed: {N}
  Result: {PASS | ISSUES_FOUND}
  Findings: {critical} critical, {major} major, {minor} minor

  {If ISSUES_FOUND, list top findings}
```

If `REVIEW_RESULT: PASS`, inform the user and stop.

If `REVIEW_RESULT: ISSUES_FOUND`, proceed based on the user's auto-fix preference already collected in Step 1 (there is a single decision point — do not re-ask here):
- **Report only**: Display all findings and stop
- **Fix Critical+Major**: auto-fix significant issues — proceed to Step 6
- **Fix all**: auto-fix everything — proceed to Step 6

### Step 6: Auto-Fix (Iterative)

**Convergence, not a fixed count**: iterate fix → re-review until the review passes or a round yields no net reduction in findings (typically 1–2 rounds). Stop and report the remaining issues as soon as a round makes no progress — do not keep looping on findings the fixer cannot resolve.

#### 6.1 Apply Fixes

For each finding to fix:

1. Read the target file
2. Apply the concrete fix described in the finding
3. Rules:
   - Only modify the specific section cited in the finding
   - Do NOT restructure or rewrite entire documents
   - Do NOT add new documents — only fix existing ones
   - If a fix requires information you don't have (e.g., specific domain logic), add a `<!-- REVIEW: {question} -->` comment instead of guessing
   - Do NOT change content unrelated to the findings

#### 6.2 Re-Review

After all fixes are applied, re-run the review (Step 3-4) on the same documents.

- **If `REVIEW_RESULT: PASS`**: Display success
  ```
  spec-forge review: PASS after fixes — {N} issues resolved
  ```

- **If `REVIEW_RESULT: ISSUES_FOUND`** (a re-review round yielded no net reduction in findings): Display remaining issues and stop
  ```
  spec-forge review: {N} issues remain after auto-fix

  Remaining issues:
    - [{severity}] {file} § {section}: {description}
    ...

  These may require manual attention or domain-specific decisions.
  ```

### Step 7: Summary

Display final status:

```
spec-forge review complete: {feature_name}

  Documents reviewed: {N}
  Issues found: {total}
  Issues fixed: {fixed}
  Issues remaining: {remaining}

Next steps:
  /code-forge:plan @docs/features/{component-name}.md   → Generate implementation plan
  /spec-forge:review {feature_name}                      → Re-run review after manual fixes
```

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