Process Pr Reviews logo

Process Pr Reviews

OrganizationPopular
nexu-io
process-pr-reviews

Use when the user asks to process, triage, fetch, view, count, list, or resolve review feedback in a GitHub PR. Supports both CodeRabbit and Codex review workflows. In this workflow, “real review feedback” is strictly defined as actionable inline comments; for CodeRabbit, exclude review summaries and nitpicks, and for Codex, exclude review summary cards and use PR main-thread reactions only as status signals.

Overview

Publishernexu-io
Repositorynexu
Skill nameprocess-pr-reviews
Stars
3.3K
Forks
262
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 nexu-io on GitHub. Read the source before you install it.

Installation

Install the Process Pr Reviews 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/nexu-io/nexu/tree/main/.agents/skills/process-pr-reviews
  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/nexu-io/nexu.git /tmp/nexu
mkdir -p .claude/skills
cp -r /tmp/nexu/.agents/skills/process-pr-reviews .claude/skills/process-pr-reviews
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Process Pr Reviews 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 Process Pr Reviews 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 Process Pr Reviews 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.

Process PR Reviews

This workflow supports both CodeRabbit and Codex PR review signals.

CodeRabbit Reviews

“Real review feedback” is strictly defined as:

  • inline review comments
  • not a review summary
  • not a nitpick

Nitpick comments from CodeRabbit must always be ignored to avoid unnecessary noise.

There is no need to analyze the comment content itself.

Data sources

The CodeRabbit workflow only needs these two sources:

  1. PR review comments

    bash
    gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/comments

    This is the authoritative source for real inline comments.

  2. PR reviews

    bash
    gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/reviews

    This is only used to identify and exclude review summaries / nitpick summaries. It is not used to extract the final result.

Do not treat these as primary sources:

  • gh pr view ...
  • gh api repos/<owner>/<repo>/issues/<pr_number>/comments

Reason: they are not the authoritative source for actionable inline comments.

Workflow

0. Optional: fetch review thread IDs early if resolve/dismiss may be needed

If the user may ask you to resolve review conversations after triaging them, fetch review thread IDs as soon as you know the PR number:

bash
gh api graphql -f query='query { repository(owner: "<owner>", name: "<repo>") { pullRequest(number: <pr_number>) { reviewThreads(first: 100) { nodes { id isResolved comments(first: 20) { nodes { databaseId path line author { login } body } } } } } } }'

This is not a primary source for actionable review feedback. It is only for mapping inline comments to resolvable thread IDs.

Recommendation:

  • If the user only wants to view/list/count review feedback, this step is optional.
  • If the user may want to resolve conversations, doing this early is usually more convenient because you can map comment databaseId / path / line to thread IDs in one pass.
1. Fetch inline comments
bash
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/comments

Only keep records that satisfy all of the following:

  • user.login is coderabbitai[bot] or coderabbitai
  • in_reply_to_id == null (only top-level inline comments, not replies)

This is the candidate set.

2. Fetch reviews to exclude review summaries / nitpicks
bash
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/reviews

Identify CodeRabbit review summaries. Common characteristics include:

  • Actionable comments posted: N
  • Nitpick comments
  • long summary text

These review-level contents are not the final result. They are only used to help determine:

  • which items are summaries
  • which nitpicks should not be counted as actionable inline comments

Filtering rule

The final goal of the CodeRabbit workflow is always:

Top-level inline comments left by CodeRabbit in pulls/<pr_number>/comments that are neither nitpicks nor summaries

Important:

  • Treat CodeRabbit nitpicks as non-actionable by default.
  • Do not include nitpicks in counts, summaries, or resolution queues unless the user explicitly asks for nitpicks.

In practice, do the following:

  1. Get CodeRabbit top-level inline comments from pulls/<pr_number>/comments
  2. Use pulls/<pr_number>/reviews to determine whether the PR contains nitpick summaries
  3. In the output, keep only the inline comments you confirm are actionable

Large output handling

If the output of gh api --paginate ... is too large and gets truncated:

  1. Record the tool output file path
  2. Do not manually read through the entire large JSON blob
  3. Hand it off to @explorer to extract:
    • CodeRabbit-authored comments
    • the number of top-level inline comments
    • each comment’s path / line / body

Resolving review conversations

Resolution policy

When triaging review feedback, apply this rule:

  • If a comment will not be fixed, you may resolve the conversation after triage.
  • If a comment will be fixed, do not resolve it first — make the code change first, then resolve the conversation afterward.

In short:

  • won't fix / no code change → triage, then resolve
  • will fix / code change required → fix first, then resolve

If the user asks to resolve a CodeRabbit review conversation:

  1. Identify the target inline comment from the actionable comment list.
  2. Map that comment to its review thread ID via reviewThreads GraphQL data.
    • Match using databaseId when possible.
    • If needed, fall back to path + line + author login.
  3. Resolve the thread with GraphQL:
bash
gh api graphql -f query='mutation { resolveReviewThread(input: {threadId: "<thread_id>"}) { thread { isResolved } } }'

Notes:

  • Resolve the thread, not the individual comment.
  • pulls/<pr_number>/comments remains the source of truth for identifying actionable inline comments.
  • reviewThreads is only for thread-level operations such as resolving conversations.

Codex Reviews

“Real review feedback” is strictly defined as:

  • inline review comments
  • not the review summary card

There is no need to analyze the comment content itself.

Important behavior differences from CodeRabbit

  • Codex review is silent while running.
  • Unlike CodeRabbit, Codex does not expose an in-progress PR check for review status.
  • While Codex is reviewing, the PR main conversation thread gets an eyes reaction from chatgpt-codex-connector[bot].
  • If Codex finds no issues, it may leave no actionable inline comments and instead react to the PR main conversation thread with +1 (thumbs up).
  • If Codex finds issues, it may create inline review comments in pulls/<pr_number>/comments and a review summary card in pulls/<pr_number>/reviews.

Data sources

The Codex workflow uses these sources:

  1. PR review comments

    bash
    gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/comments

    This is the authoritative source for actionable inline Codex comments.

  2. PR reviews

    bash
    gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/reviews

    This is used to identify the Codex review summary card such as ### 💡 Codex Review. It is not the primary source of actionable inline feedback.

  3. Issue comment reactions on the PR main thread

    First fetch the PR issue node / comments if needed:

    bash
    gh api repos/<owner>/<repo>/issues/<pr_number>/comments
    gh api repos/<owner>/<repo>/issues/<pr_number>/reactions

    Use reactions on the PR main conversation thread only to detect Codex review state:

    • eyes from chatgpt-codex-connector[bot] → Codex review appears to be in progress
    • +1 from chatgpt-codex-connector[bot] on the PR main thread → Codex reviewed and found no issues

    These reactions are status signals, not actionable review feedback.

Do not treat these as primary sources for actionable comments:

  • gh pr view ...
  • gh api repos/<owner>/<repo>/issues/<pr_number>/comments
  • gh api repos/<owner>/<repo>/issues/<pr_number>/reactions

Reason: actionable Codex review feedback still lives in PR review comments, not in the PR issue timeline.

Workflow

1. Fetch inline comments
bash
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/comments

Only keep records that satisfy all of the following:

  • user.login is chatgpt-codex-connector[bot]
  • in_reply_to_id == null (only top-level inline comments, not replies)

This is the candidate set of actionable Codex comments.

2. Fetch reviews to identify the summary card
bash
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/reviews

Identify Codex review summaries. Common characteristics include:

  • ### 💡 Codex Review
  • explanatory text such as Here are some automated review suggestions for this pull request.
  • “About Codex in GitHub” help text

These review-level contents are not the final result. They are only used to understand whether Codex posted a review summary.

3. Optionally inspect PR main-thread reactions for status

If the user asks whether Codex is still reviewing, or whether Codex finished with no findings, inspect reactions on the PR main thread.

Interpret them as follows:

  • eyes by chatgpt-codex-connector[bot] → likely still reviewing / review in progress
  • +1 by chatgpt-codex-connector[bot] with no Codex inline comments → likely completed with no findings

Do not count these reactions as review comments.

Filtering rule

The final goal of the Codex workflow is always:

Top-level inline comments left by Codex in pulls/<pr_number>/comments

In practice, do the following:

  1. Get Codex top-level inline comments from pulls/<pr_number>/comments
  2. Use pulls/<pr_number>/reviews only to recognize the summary card
  3. If there are no Codex inline comments, optionally inspect PR main-thread reactions to distinguish:
    • still reviewing (eyes)
    • reviewed with no findings (+1)
    • no observable Codex activity

Large output handling

If any gh api --paginate ... output is too large and gets truncated:

  1. Record the tool output file path
  2. Do not manually read through the entire large JSON blob
  3. Hand it off to @explorer to extract:
    • Codex-authored inline comments
    • the number of top-level inline comments
    • each comment’s path / line / body

Frequently asked questions

What does the Process Pr Reviews AI skill do?

Use when the user asks to process, triage, fetch, view, count, list, or resolve review feedback in a GitHub PR. Supports both CodeRabbit and Codex review workflows. In this workflow, “real review feedback” is strictly defined as actionable inline comments; for CodeRabbit, exclude review summaries and nitpicks, and for Codex, exclude review summary cards and use PR main-thread reactions only as status signals.

Why use Process Pr Reviews on TypingMind?

Because you install it once and use it with any model. Process Pr Reviews 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 Process Pr Reviews in TypingMind?

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

Which AI models can use Process Pr Reviews?

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 Process Pr Reviews?

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

Is the Process Pr Reviews AI skill free?

Yes. It is published on GitHub by nexu-io 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇