evalstate/fast-agent/pr-writing-review
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Checking that the SKILL.md file is still in the repository.
Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer suggestions to help refine future writing.
Install
npx vskill@latest install evalstate/fast-agent/pr-writing-reviewSKILL.md
PR Writing Review
Extract editorial feedback from GitHub PRs to learn from review improvements.
Prerequisites
- GitHub CLI:
ghinstalled - Authenticated `gh` session:
gh auth statusshould show you’re logged in - For private repos, your token needs appropriate scopes (typically
repo). - Python: 3.12+
- uv (recommended): https://github.com/astral-sh/uv
Division of Labor
| Tool | Responsibility | |
|---|---|---|
| Python script | API calls, parsing, file tracking across renames, structured extraction | |
| LLM analysis | Pattern recognition, paragraph comparison, style lesson synthesis |
Quick Start
Workflow
Step 1: Extract with --diff
This outputs:
- Explicit Suggestions — exact before/after text from
suggestionblocks (supports multiple suggestion blocks per comment) - Reviewer Feedback — plain text comments (the "why" behind changes)
- File Evolution — first draft and final version of each text file
Tip: add--max-file-chars 2000to keep each FIRST/FINAL dump lightweight, or pair--diffwith--no-filesif you only need the suggestion/feedback summaries.
Step 2: Analyze the Output
With the script output, perform this analysis:
A. Catalog the Explicit Suggestions
Create a table of mechanical fixes:
| Pattern | Original | Fixed | |
|---|---|---|---|
| Grammar | "Its easier" | "It's easier" | |
| Filler removal | "using this way" | "this way" | |
| Capitalization | "Image Generation" | "image generation" |
B. Map Feedback to Changes
For each reviewer feedback comment:
- Find the relevant section in FIRST DRAFT
- Find the same section in FINAL VERSION
- Document what changed and why
Example:
Feedback: "would be nice to end more enthusiastically"First draft: "...it's simple to add new tools to Claude and use them straight away."Final: "...Let us know what you find and create in the comments below!"Lesson: End blog posts with a call-to-action
C. Paragraph-by-Paragraph Comparison
Compare FIRST DRAFT to FINAL VERSION section by section:
- What was added?
- What was removed?
- What was reworded?
- What structural changes were made?
D. Synthesize Style Patterns
Group findings into categories:
| Category | Patterns Found | |
|---|---|---|
| Clarity | Passive→active, shorter sentences, remove filler | |
| Precision | Vague→specific, "Create"→"Generate" | |
| Tone | Added enthusiasm, call-to-action endings | |
| Structure | Added transitions, better section flow | |
| Grammar | its/it's, subject-verb agreement | |
| Content | Added links, examples, context |
Script Options
📁 All paths are relative to the directory containing this SKILL.md file.
| Flag | Output | Use Case | |
|---|---|---|---|
| _(none)_ | Suggestions + feedback | Quick review of what reviewers said | |
--diff | Adds FIRST/FINAL file dumps to the default output | Deep analysis of how the author responded | |
--max-file-chars N | Truncates each FIRST/FINAL block to _N_ chars (appends ...[truncated X chars]) | Keep prompts within LLM token limits | |
--no-files | Suppresses FIRST/FINAL dumps even when --diff is set | When you only need explicit suggestions + reviewer feedback | |
--json | Raw JSON (includes file_evolutions when --diff without --no-files) | Programmatic processing |
Input formats: pass either a full PR URL,owner/repo PR_NUMBER, orowner repo PR_NUMBER.
Output Structure
Default Output
- Writing Suggestions: Grouped by reviewer, shows original→suggested text (fenced blocks) along with any reviewer note and a permalink back to GitHub
- Reviewer Feedback: Plain comments without code suggestions, each tagged with its GitHub link
With --diff
- Explicit Suggestions: Compact before/after pairs, reviewer notes, and GitHub permalinks in one place
- Reviewer Feedback: Numbered list of requests (same as default view)
- File Evolution: FIRST DRAFT and FINAL VERSION for each
.md/.txt/.rst/.mdxfile; add--max-file-charsto truncate each block with a visible...[truncated X chars]indicator
Handling File Renames
The script traces files through renames by:
- Checking each commit for rename operations
- Building a path history (e.g.,
claudeimages.md→claude-images.md→claude-and-mcp.md) - Fetching content using the correct path for each commit
Example Analysis Output
After running the script and performing LLM analysis, produce a summary like:
Limitations
- Only extracts inline PR review comments (not issue comments or the PR description)
- Extremely long files can still be heavy; when that happens, lower
--max-file-charsor pass--no-filesto keep outputs prompt-friendly
{{currentDate}} {{env}}
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingexamples/hf-toad-cards/skills/pr-writing-review/SKILL.md
Popularity
- Repository stars
- 3,704
- Repository forks
- 394
- 7-day trend score
- 41
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 19 Mar 2026, 7 months ago.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
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