docs-review

metabase/metabase · updated Apr 8, 2026

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$npx skills add https://github.com/metabase/metabase --skill docs-review
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summary

@./../_shared/metabase-style-guide.md

skill.md

Documentation Review Skill

@./../_shared/metabase-style-guide.md

Review mode detection

IMPORTANT: Before starting the review, determine which mode to use:

  1. PR review mode: If the mcp__github__create_pending_pull_request_review tool is available, you are reviewing a GitHub PR

    • Use the pending review workflow to post all issues as one cohesive review
    • Follow the workflow steps in "PR review mode format" below
  2. Local review mode: If the MCP tool is NOT available, output issues in the conversation

    • Format all issues in a numbered markdown list (as described in "Feedback format" below)

Review process

  1. Detect review mode - Check if mcp__github__create_pending_pull_request_review is available
  2. Read the changes through once to understand intent
  3. Check all issues that violate style guide or significantly impact readability
  4. Only flag issues worth mentioning - if it won't make a material difference to the reader, skip it
  5. REQUIRED: Number ALL feedback sequentially - Start from Issue 1 and increment for each issue found

Review checklist

Run through the diff looking for these issues:

Tone and voice:

  • Formal/corporate language ("utilize" not "use", "offerings", etc.)
  • "Users" instead of "people" or "companies"
  • Excessive exclamation points or overly peppy tone
  • Telling readers something is cool instead of showing them

Structure and clarity:

  • Important information buried instead of leading
  • Verbose text that adds little value
  • Paragraphs without clear purpose
  • Vague headings that don't convey the point
  • Instructions explain "why" before telling "what to do"
  • Tasks described as "easy" or "simple"

Links and references:

  • Linking the word "here" instead of descriptive text
  • Links in headings (unless entire heading is a link)

Formatting:

  • Ampersands as "and" substitute (except proper nouns)
  • Inconsistent list formatting

Code and examples:

  • Code examples that don't work or would error
  • Commands not in execution order
  • Full-width screenshots instead of scoped UI elements
  • Excessive or unnecessary images

Sentence construction:

  • Overuse of pronouns when introducing new terms

Quick scan table

Pattern Issue
we can do X, our feature Should be "Metabase" or "it"
click here, read more here Need descriptive link text
easy, simple, just Remove condescending qualifiers
users Should be "people" or "companies" if possible

Feedback format

MANDATORY REQUIREMENT: Every single issue MUST be numbered sequentially starting from Issue 1.

This numbered format is NON-NEGOTIABLE. It allows users to efficiently reference specific issues (e.g., "fix issues 1, 3, and 5") and track which feedback has been addressed.

Local review mode format

When outputting issues in the conversation (local mode), use this format:

## Issues

**Issue 1: [Brief title]**
Line X: Succinct description of the issue
[code or example]
Suggested fix or succinct explanation

**Issue 2: [Brief title]**
Line Y: Description of the issue
Suggested fix or explanation

**Issue 3: [Brief title]**
...

Examples:

Issue 1: Formal tone Line 15: This could be more conversational. Consider: "You can't..." instead of "You cannot..."

Issue 2: Vague heading Line 8: The heading could be more specific. Try stating the point directly: "Run migrations before upgrading" vs "Upgrade process"

PR review mode format

When posting to GitHub (PR mode), use the pending review workflow:

Workflow steps:

  1. Start a review: Use mcp__github__create_pending_pull_request_review to begin a pending review

    • This creates a draft review that won't be visible until submitted
  2. Get diff information: Use mcp__github__get_pull_request_diff to understand the code changes and line numbers

    • This helps you determine the correct file paths and line numbers for comments
  3. Identify ALL issues: Read through all changes and identify every issue worth mentioning

    • Collect all issues before posting any comments
    • Number them sequentially (Issue 1, Issue 2, Issue 3, etc.)
  4. Add review comments: Use mcp__github__add_pull_request_review_comment_to_pending_review for each issue

    • CRITICAL: Post ALL comments in a SINGLE response using multiple tool calls in parallel
    • Each comment should reference a specific file path and line number from the diff
    • Start each comment body with **Issue N: [Brief title]**
    • Include the description and suggested fix
  5. Submit the review: Use mcp__github__submit_pending_pull_request_review to publish all comments at once

    • Use event type "COMMENT" (NOT "REQUEST_CHANGES") to make it non-blocking
    • Do NOT include a body message - Leave the body empty or omit it entirely
    • All comments will appear together as one cohesive review

Comment format example:

**Issue 1: Formal tone**

This could be more conversational. Consider: "You can't..." instead of "You cannot..."

IMPORTANT:

  • Each issue gets its own review comment attached to the pending review
  • Number ALL comments sequentially (Issue 1, Issue 2, Issue 3, etc.)
  • Always start the comment body with **Issue N: [Brief title]**
  • MUST add all comments in parallel in a single response - Do NOT add them one after another in separate responses
  • Do NOT output a summary message to the conversation - only post GitHub review comments
  • When submitting the review, do NOT include a body parameter (or leave it empty) to avoid cluttering the PR with summary text
  • The review will appear as a single review with multiple comments when submitted

Final check

  1. Remove any issues from your assessment that won't make a material difference to the reader if addressed. Only flag issues worth the author's time to fix.
  2. Verify all issues are numbered sequentially starting from Issue 1 with no gaps in numbering.
  3. Confirm the format exactly matches: **Issue N: [Brief title]** where N is the issue number.
  4. In PR mode: Verify each issue was posted as a separate GitHub comment (not output to conversation).
how to use docs-review

How to use docs-review on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add docs-review
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/metabase/metabase --skill docs-review

The skills CLI fetches docs-review from GitHub repository metabase/metabase and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/docs-review

Reload or restart Cursor to activate docs-review. Access the skill through slash commands (e.g., /docs-review) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ 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.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.848 reviews
  • Dhruvi Jain· Dec 28, 2024

    docs-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Meera Thompson· Dec 28, 2024

    Useful defaults in docs-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Noor Shah· Dec 8, 2024

    docs-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Naina Li· Dec 4, 2024

    Keeps context tight: docs-review is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Ava Khanna· Nov 27, 2024

    Useful defaults in docs-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Meera Robinson· Nov 23, 2024

    I recommend docs-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· Nov 19, 2024

    Registry listing for docs-review matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aanya Diallo· Nov 19, 2024

    docs-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noor Khanna· Nov 19, 2024

    Solid pick for teams standardizing on skills: docs-review is focused, and the summary matches what you get after install.

  • Lucas Reddy· Oct 18, 2024

    I recommend docs-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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