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Fetch Pr Comments

Community
tobihagemann
fetch-pr-comments

Fetch and summarize review feedback and conversation from a GitHub PR (unresolved review threads, review bodies, and PR conversation comments) without making changes. Use when the user asks to "fetch PR comments", "show PR comments", "check PR for unresolved comments", "list review comments", "what comments are on the PR", "show unresolved threads", or "summarize PR feedback".

Overview

Publishertobihagemann
Repositoryturbo
Skill namefetch-pr-comments
Stars
417
Forks
32
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Fetch Pr Comments 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/tobihagemann/turbo/tree/main/claude/skills/fetch-pr-comments
  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/tobihagemann/turbo.git /tmp/turbo
mkdir -p .claude/skills
cp -r /tmp/turbo/claude/skills/fetch-pr-comments .claude/skills/fetch-pr-comments
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fetch Pr Comments 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 Fetch Pr Comments 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 Fetch Pr Comments 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.

Fetch PR Comments

Fetch unresolved review comments, top-level review body comments, and PR conversation comments from a GitHub PR and present them in a readable summary. This is a read-only skill -- it does not evaluate, fix, or reply to any comments.

Step 1: Fetch Comments

Auto-detect owner, repo, and PR number from current branch if not provided. Then run scripts/fetch-pr-data.sh, which handles full pagination (review threads, inner comment pages for long threads, reviews, issue comments) and emits a single merged JSON document:

bash
bash <skill-dir>/scripts/fetch-pr-data.sh <owner> <repo> <pr_number>

Output shape:

jsonc
{
  "meta":          { "title", "url", "headRefName", "baseRefName" },
  "reviewThreads": [ { "id", "isResolved", "isOutdated", "comments": { "nodes": [ { "author", "body", "path", "line", "originalLine", "diffHunk" } ] } } ],
  "reviews":       [ { "author", "body", "state" } ],
  "issueComments": [ { "author", "body", "createdAt", "url" } ]
}

Filter review threads to unresolved only. Filter reviews to those with a non-empty body, excluding PENDING state (unsubmitted drafts). Filter issue comments to those with a non-empty body.

Step 2: Present Results

Display a summary header followed by comments grouped by file.

Summary header:

  • PR title and link
  • Branch: head -> base
  • Total threads / unresolved threads

Top-level review comments (if any):

Show reviews with non-empty body before the file-grouped threads:

## Review Comments

### @reviewer (CHANGES_REQUESTED)
> Review body text here

### @another-reviewer (COMMENTED)
> Another review body here

Issue comments (if any):

Show PR conversation comments after review comments, ordered by createdAt:

## Issue Comments

### @commenter (2026-04-20)
> Issue comment body here

### @another-commenter (2026-04-21)
> Another issue comment body here

Inline threads grouped by file:

For each file with unresolved threads, show:

## `path/to/file.ts`

### Line 42 (by @reviewer)
```diff
<diffHunk from first comment>
```
> Comment body here

### Line 10 (by @another-reviewer) [outdated]
```diff
<diffHunk from first comment>
```
> First comment body
>
> **@reply-author:** Reply body

Formatting rules:

  • Show top-level review body comments first, grouped under "Review Comments"
  • Show PR conversation comments next, grouped under "Issue Comments", ordered by createdAt
  • Then group threads by file path, in the order they appear
  • Within each file, order threads by line number
  • Show the diffHunk from the first comment in each thread as a fenced diff code block before the comment body. This is the code context the reviewer was looking at.
  • For the line number, use line if available. Fall back to originalLine for outdated comments where line is null.
  • Show all comments in a thread (the first is the original review comment; subsequent ones are replies)
  • Mark outdated threads with [outdated]
  • Use blockquotes for comment bodies
  • For threads with multiple comments, show each comment with its author
  • If there are zero unresolved threads, zero review body comments, and zero issue comments, say so and stop

Then use the TaskList tool and proceed to any remaining task.

Rules

  • If the user wants to fix or reply to comments, direct them to use /resolve-pr-comments.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Fetch Pr Comments AI skill do?

Fetch and summarize review feedback and conversation from a GitHub PR (unresolved review threads, review bodies, and PR conversation comments) without making changes. Use when the user asks to "fetch PR comments", "show PR comments", "check PR for unresolved comments", "list review comments", "what comments are on the PR", "show unresolved threads", or "summarize PR feedback".

Why use Fetch Pr Comments on TypingMind?

Because you install it once and use it with any model. Fetch Pr Comments 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 Fetch Pr Comments in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tobihagemann/turbo/tree/main/claude/skills/fetch-pr-comments. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Fetch Pr Comments?

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 Fetch Pr Comments?

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

Is the Fetch Pr Comments AI skill free?

Yes. It is published on GitHub by tobihagemann 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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