| name | review |
| description | Review spec-forge generated documents (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 (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.
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Review — Specification Quality & Consistency Review
Systematically review spec-forge generated documents for quality, completeness, and internal consistency. Optionally auto-fix issues found.
Core Principles
- Evidence-based: Every finding must cite a specific file and section — no vague complaints
- Spec-focused: Review specification documents only (tech-design, feature specs, overview) — not code, not upstream idea drafts
- Upstream-aware: Use idea drafts and project manifests as reference context to validate spec accuracy, but do not review them
- Prioritized: Findings classified by severity so the user can act on what matters first
- Conservative fixes: Auto-fix only touches cited sections; when domain knowledge is missing, leave a
<!-- REVIEW: {question} --> comment instead of guessing
- 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:
- If a
feature_name argument is provided, look for:
docs/{feature_name}/tech-design.md
- All feature specs in
docs/features/ (glob for docs/features/*.md)
- Upstream reference:
ideas/{feature_name}/draft.md (if exists)
- Project manifest:
docs/project-{feature_name}.md (if exists, for multi-split context)
- If no argument, scan
docs/ for the most recent tech-design and all feature specs in docs/features/
- 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 / 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:
-
Review targets (will be reviewed):
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
-
Reference context (read for context, NOT reviewed):
ideas/{feature_name}/draft.md — upstream requirements
docs/project-{feature_name}.md — project manifest with sub-feature scope
-
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 —
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?
- 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
3.2 Internal Consistency
-
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 —
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:
- Read the target file
- Apply the concrete fix described in the finding
- 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