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Pr Review

Community
poshan0126
pr-review

Review code changes or a pull request. Delegates to specialist agents (code quality, security, performance, silent failures, test quality, docs) in parallel.

Overview

Publisherposhan0126
Repositorydotclaude
Skill namepr-review
Stars
870
Forks
204
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by poshan0126 on GitHub. Read the source before you install it.

Installation

Install the Pr Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/poshan0126/dotclaude/tree/main/skills/pr-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/poshan0126/dotclaude.git /tmp/dotclaude
mkdir -p .claude/skills
cp -r /tmp/dotclaude/skills/pr-review .claude/skills/pr-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Pr Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Pr Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Review code changes by delegating to specialist agents in parallel and synthesizing a unified report. Works with PRs, staged changes, or specific files.

Verbosity

Check $ARGUMENTS for the word verbose. Strip it from the argument string before parsing the rest.

  • Default: terse output. Each finding is one line (file:line: issue (fix: hint)). Synthesis report stays compact.
  • verbose: full breakdown. Each finding gets the multi-field block (Severity, Confidence, etc.). Synthesis report uses the full template.

When dispatching reviewers in Step 3, include the word verbose in each Task call's prompt only if the user asked for it. Otherwise omit; the reviewers default to terse.

Step 1: Determine Scope

Parse $ARGUMENTS to determine what to review:

  • PR number (e.g., 123 or #123): fetch with gh pr view $ARGUMENTS. This is the full PR review path (includes PR quality checks in Step 2).
  • No argument: try gh pr view to detect a PR for the current branch. If a PR exists, use it. If not, fall back to git diff --cached (staged), then git diff (unstaged).
  • staged: review git diff --cached. If nothing staged, fall back to git diff.
  • File path: review that specific file's current state.

If there are no changes to review, say so and stop.

Step 2: PR Quality Check (PR path only)

Skip this step if reviewing staged changes or a file. Jump to Step 3.

When reviewing a PR, fetch and check:

  • PR title, description/body, author, base branch, head branch
  • gh pr diff $NUMBER for the full diff
  • gh pr checks $NUMBER for CI status
  • gh api repos/{owner}/{repo}/pulls/$NUMBER/comments for review comments

Review the PR itself before the code:

  • Title: descriptive and under 72 chars?
  • Description: explains the why? Includes a test plan? Flag if empty or template-only.
  • Size: count changed files and lines. Flag if >500 lines changed (suggest splitting).
  • Base branch: targeting the right branch?
  • CI status: passing, failing, or pending? If failing, note which checks. Fix CI first.
  • Unresolved comments: list open review threads with file:line and comment text.

Step 3: Code Review (fan out to specialists in parallel)

Decide which reviewers apply by reading the diff content, not just file paths:

ReviewerWhen to include
code-reviewerAlways. Universal correctness pass.
silent-failure-hunterAny diff touching error handling, catch blocks, fallbacks, retries, or async flows. In practice: almost every code diff. Skip only for pure-docs, config-only, or static-asset diffs.
pr-test-analyzerTests were added or changed, OR behavior changed without any test change (that absence is itself the finding). Skip for pure-docs or config diffs.
security-reviewerAuth, input handling, queries, tokens, session management, file path construction, SQL or HTML or template strings.
performance-reviewerEndpoints, DB queries, loops over collections, caching, connection management. Skip for pure-docs, config-only, or static-asset diffs.
doc-reviewer.md changes, significant docstring or JSDoc changes, API docs.

Dispatch all applicable reviewers in PARALLEL. Send one message that contains one Agent/Task tool call per applicable reviewer. Do NOT invoke them sequentially. Parallel dispatch cuts wall-clock time from N times the slowest review to roughly the slowest single review, with no extra token cost. Each call looks like:

Agent(subagent_type: "code-reviewer",
      prompt: "Review <scope>. <verbose?> Output one confidence score (0-100) per finding.")

Ask every reviewer to attach a confidence score per finding — Step 4 uses them.

If only one reviewer applies (a pure-docs diff, for example), a single Task call is fine. Skip the parallel pattern when there's nothing to parallelize.

While the reviewers run, you can read the PR description, recent CI logs, or open comments to enrich the synthesis in Step 4. Don't wait idly.

Step 4: Synthesize Report

Use the terse template by default. Use the verbose template only if the user passed verbose.

Default (terse)

For PR reviews:

## PR Review: #[number]: [title]

[base] -> [head]. [N files, +X/-Y lines]. CI: [pass | fail: <checks>]. PR quality: [ok | issues: <list>].

### Findings ([N])
- [agent] file:line: issue (fix: hint)
- [agent] file:line: issue (fix: hint)

### Verdict
[Ready to merge | Needs changes: <one-line blocker>]

For non-PR reviews (staged or file):

## Review ([scope])

[N findings from <agents>]:
- [agent] file:line: issue (fix: hint)
- [agent] file:line: issue (fix: hint)

If no findings, output a single line: "No issues found across [agents]."

Verbose (when the user passed verbose)

For PR reviews:

## PR Review: #[number]: [title]

**Author**: [author] | **Base**: [base] -> **Head**: [head] | **Changed**: [N files, +X/-Y lines]

### PR Quality
- Title: [ok / needs improvement]
- Description: [ok / missing test plan / empty]
- Size: [ok / large, consider splitting]
- CI: [passing / failing, list failures]
- Unresolved comments: [none / list]

### Code Review
#### Critical / High
- [Agent] File:Line: issue

#### Medium
- [Agent] File:Line: issue

#### Low
- [Agent] File:Line: issue

### Verdict
[Ready to merge / Needs changes, summarize blockers]

For non-PR reviews (staged or file):

## Review Summary

**Scope**: [staged changes / file path]
**Agents run**: [list]

### Critical / High
- [Agent] File:Line: issue

### Medium / Low
- [Agent] File:Line: issue

### Passed
- [areas with no issues]

Merging, confidence, and deconfliction (both templates)

  • Deduplicate findings that overlap between agents; attribute the merged finding to the agent with the most specific evidence.
  • Confidence buckets: 90-100 → report as findings to act on; 80-89 → report under a Consider subheading; anything an agent shipped below 80 shouldn't exist — drop it.
  • Deconfliction: when two agents flag the same lines with different fixes, prefer the more specific domain — security-reviewer over code-reviewer on input handling; performance-reviewer over code-reviewer on complexity if the path is hot, code-reviewer otherwise; silent-failure-hunter over code-reviewer on error handling. Never present two conflicting fixes for the same lines without saying which to apply.
  • Attribute each finding to the agent that found it.

Frequently asked questions

What does the Pr Review AI skill do?

Review code changes or a pull request. Delegates to specialist agents (code quality, security, performance, silent failures, test quality, docs) in parallel.

Why use Pr Review on TypingMind?

Because you install it once and use it with any model. Pr Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Pr Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/poshan0126/dotclaude/tree/main/skills/pr-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pr Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Pr Review?

As many as you like. As long as a model supports skills, you can use Pr Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Pr Review AI skill free?

Yes. It is published on GitHub by poshan0126 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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