review-docs
npx skills add https://github.com/tldraw/tldraw --skill review-docs
Agent 安装分布
Skill 文档
Review documentation
This skill runs an evaluation and improvement loop on a documentation file.
Target: $ARGUMENTS
Relevant skills: write-docs
Workflow overview
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â INITIALIZE: Create state file to track issues â
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â EVALUATE (parallel) â
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â â Style Agent â â Content Agent â â
â â (readability+voice) â â (completeness+accuracy) â â
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â UPDATE STATE: Add new issues, verify fixed issues â
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â SUMMARIZE: Present findings, ask user for next step â
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[User: improve] [User: complete] [User: done]
â â â
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â IMPROVE â â COMPLETE â
â (fix issues) â â (fix all, exit) â
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LOOP â EVALUATE EXIT
State file
Create a state file in the scratchpad directory to track all issues across rounds. This prevents re-discovering the same issues and allows verification of fixes.
Path: <scratchpad>/review-<filename>.md
Format:
# Review tracker: [filename]
## Issue tracker
Status values: `pending` | `fixed` | `verified-fixed` | `not-fixed` | `wont-fix`
| ID | Issue | Type | Status | Round | Notes |
| --- | ------------- | --------------------------- | -------------- | ----- | ---------------- |
| 1 | [description] | Style/Accuracy/Completeness | pending | 1 | [details] |
| 2 | [description] | Accuracy | verified-fixed | 1 | Fixed in round 1 |
| 3 | [description] | Completeness | wont-fix | 2 | Out of scope |
## Round history
### Round 1
- Style: X/10, Voice: X/10, Completeness: X/10, Accuracy: X/10
- **Total: X/40**
Status definitions:
pending: Issue discovered, not yet addressedfixed: Improvement agent claims to have fixed it, needs verificationverified-fixed: Evaluation confirmed the fix was applied correctlynot-fixed: Evaluation found the fix wasn’t applied correctlywont-fix: False alarm, out of scope, or intentional (e.g., completeness issues that require documentation expansion)
Step 1: Initial evaluation
For the first round, launch two subagents in parallel using the Task tool:
// Single message with two Task tool calls:
Task(subagent_type="general-purpose", model="opus", prompt="Style evaluation...")
Task(subagent_type="general-purpose", model="opus", prompt="Content evaluation...")
Style agent prompt (round 1)
Evaluate documentation style for: $ARGUMENTS
Read these files:
1. .claude/skills/shared/writing-guide.md
2. .claude/skills/shared/docs-guide.md
3. $ARGUMENTS
Score these dimensions (0-10):
READABILITY - How clear and easy to understand is the writing?
- Clear, direct sentences
- Logical flow between sections
- Appropriate use of code snippets and links
- No unnecessary jargon
VOICE - How well does it follow the writing guide?
- Confident assertions (no hedging)
- Active voice, present tense
- No AI writing tells (hollow importance, trailing gerunds, formulaic transitions)
- Appropriate tone (expert-to-developer)
- Sentence case headings
Important! Include as many high-priority fixes as needed.
Return in this exact format:
STYLE REPORT: [filename]
READABILITY: [score]/10
- [specific issue or strength]
- [specific issue or strength]
VOICE: [score]/10
- [specific issue or strength]
- [specific issue or strength]
PRIORITY FIXES:
1. [Most important style issue]
2. [Second most important]
3. [Third most important]
4. ...
Content agent prompt (round 1)
Evaluate documentation content for: $ARGUMENTS
Read $ARGUMENTS, then verify claims against the source code in packages/editor/ and packages/tldraw/.
Score these dimensions (0-10):
COMPLETENESS - How thorough is the coverage?
- Overview establishes purpose before mechanism
- Key concepts explained with enough depth
- Illustrative code snippets where needed
- Links to relevant examples in apps/examples (if applicable)
ACCURACY - Is the technical content correct?
- Code snippets are syntactically correct and use valid APIs
- API references match actual implementation
- Described behavior matches the code
- No outdated information
For accuracy issues, include file:line references to the source code.
Important! Include as many high-priority fixes as needed. Make sure that all accuracy issues are flagged.
Return in this exact format:
CONTENT REPORT: [filename]
COMPLETENESS: [score]/10
- [specific issue or strength]
- [specific issue or strength]
ACCURACY: [score]/10
- [specific issue with file:line reference if inaccurate]
- [specific issue or strength]
PRIORITY FIXES:
1. [Most important content issue]
2. [Second most important]
3. [Third most important]
4. ...
After round 1, create the state file with all discovered issues.
Step 2: Summarize and prompt user
After both agents return, synthesize their reports into a summary:
## Evaluation: [filename]
| Dimension | Score | Key issue |
| ------------ | ----- | ----------- |
| Readability | X/10 | [one-liner] |
| Voice | X/10 | [one-liner] |
| Completeness | X/10 | [one-liner] |
| Accuracy | X/10 | [one-liner] |
| **Total** | X/40 | |
### Priority fixes
1. [Combined priority 1 from both reports]
2. [Combined priority 2]
3. [Combined priority 3]
4. [Combined priority 4]
5. [Combined priority 5]
6. ...
Then ask the user using AskUserQuestion:
- Improve: Make improvements based on findings, then re-evaluate
- Complete and finish: Fix all remaining issues and exit (no re-evaluation)
- Done: Exit the loop without making changes
Step 3: Triage (before improvement)
Before running the improvement agent, review the pending issues with the user. Mark completeness issues that require adding new sections as wont-fix – these are documentation expansion, not review fixes.
Per CLAUDE.md guidance:
“Do what has been asked; nothing more, nothing less.” “Don’t add features, refactor code, or make ‘improvements’ beyond what was asked.”
The review skill improves existing content. Adding new sections is a separate task.
Step 4: Improve
Launch a single improvement agent targeting only pending issues:
Task(subagent_type="general-purpose", model="opus", prompt="Improve documentation...")
Improvement agent prompt
Improve documentation based on specific tracked issues: $ARGUMENTS
Fix ONLY these pending issues:
| ID | Issue | Type | Notes |
|----|-------|------|-------|
[paste pending issues from state file]
Instructions:
1. Read .claude/skills/shared/writing-guide.md
2. Read .claude/skills/shared/docs-guide.md
3. Read $ARGUMENTS
4. For each accuracy fix:
- Read the source file referenced in the notes
- Verify the correct API/behavior from the source
- Apply the fix based on what the source code actually shows
5. Apply style fixes
6. Run prettier: yarn prettier --write $ARGUMENTS
DO NOT:
- Add new sections
- Expand the document
- Fix issues not in the list above
Return a summary:
CHANGES MADE:
| ID | Fix applied | Verification |
|----|-------------|--------------|
| X | [description] | [source file:line checked] |
| Y | [description] | n/a |
After improvement, update the state file to mark issues as fixed.
Step 4b: Complete and finish (alternative to Step 4)
If the user selects “Complete and finish”, fix all remaining pending issues without re-evaluating. This is useful when the evaluation is satisfactory and the user wants to apply fixes and move on.
Workflow:
- Run triage (same as Step 3) to mark out-of-scope items as
wont-fix - Launch the improvement agent (same prompt as Step 4)
- Update state file to mark issues as
fixed - Exit the loop – do not re-evaluate
This path trusts the improvement agent to apply fixes correctly and skips the verification cycle. Use when:
- The issues are straightforward style fixes
- Time is limited and re-evaluation isn’t worth the cost
- Scores are already acceptable and only minor polish remains
Step 5: Verification evaluation
For subsequent rounds, evaluation agents verify fixes AND find new issues:
Style agent prompt (verification)
Verify fixes and evaluate documentation: $ARGUMENTS
Read the state file first: [path to state file]
Then read:
1. .claude/skills/shared/writing-guide.md
2. .claude/skills/shared/docs-guide.md
3. $ARGUMENTS
Your job:
1. VERIFY fixes marked as "fixed" in the state file - confirm they were actually applied
2. Score style dimensions (do NOT re-flag wont-fix issues)
3. Flag only NEW issues not already in the state file
VERIFY THESE FIXES:
[paste fixed style issues from state file]
Return in this format:
VERIFICATION REPORT:
| ID | Status | Notes |
|----|--------|-------|
| X | verified-fixed / not-fixed | [what you found] |
STYLE SCORES:
READABILITY: [score]/10
VOICE: [score]/10
NEW ISSUES (not already in state file):
- [issue] or "None found"
Content agent prompt (verification)
Verify fixes and evaluate documentation content: $ARGUMENTS
Read the state file first: [path to state file]
Then read $ARGUMENTS and verify claims against source code in packages/tldraw/.
Your job:
1. VERIFY accuracy fixes marked as "fixed" in the state file
2. Score content dimensions (do NOT re-flag wont-fix issues)
3. Flag only NEW accuracy issues not already in the state file
VERIFY THESE FIXES:
[paste fixed accuracy issues from state file]
Return in this format:
VERIFICATION REPORT:
| ID | Status | Notes |
|----|--------|-------|
| X | verified-fixed / not-fixed | [what you found in doc AND source] |
CONTENT SCORES:
COMPLETENESS: [score]/10 (score existing content only, ignore wont-fix items)
ACCURACY: [score]/10
NEW ACCURACY ISSUES (not already in state file):
- [issue with source file:line] or "None found"
After verification, update the state file with new statuses and any new issues.
Step 6: Loop
Continue the loop until:
- User chooses “Done” (exit without changes)
- User chooses “Complete and finish” (apply fixes, then exit)
- Scores reach acceptable levels (32/40 or higher)
- All issues are
verified-fixedorwont-fix
Notes
- The state file prevents re-discovering the same issues across rounds
- Evaluation agents verify previous fixes before scoring
wont-fixis appropriate for completeness issues requiring new sections- Accuracy verification is critical: The improvement agent must read actual source code before applying any accuracy fix
- Style and content evaluations always run in parallel for efficiency