Pr Writer logo

Pr Writer

OrganizationPopular
getsentry
pr-writer

Create or refresh reviewer-facing PR titles and descriptions. Use when opening a PR, updating its title or body, or preparing branch changes for review.

Overview

Publishergetsentry
Repositoryskills
Skill namepr-writer
Stars
1K
Forks
53
Bundled files
4
LicenseApache-2.0
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.

  • 4 bundled files

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

  • Open source

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

Installation

Install the Pr Writer 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/getsentry/skills/tree/main/skills/pr-writer
  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/getsentry/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/pr-writer .claude/skills/pr-writer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pr Writer 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 Writer 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 Writer 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.

PR Writer

Write the PR body as a cover note for reviewers, not a changelog, template, validation log, or file-by-file summary.

Inspect the Change

Requires authenticated gh. Inspect the current branch, working tree, PR, base branch, commits, and full diff:

bash
git branch --show-current
git status --porcelain
gh pr view --json number,title,body,url,baseRefName,headRefName
gh repo view --json defaultBranchRef

If gh pr view reports that no PR exists, continue with first-time PR creation. For an existing PR, use its baseRefName; otherwise use the repository default branch. Set BASE, then inspect:

bash
git log "$BASE"..HEAD --oneline
git diff "$BASE"...HEAD

If on main or master, create a feature branch first. Ensure intended changes are committed and review the whole branch diff, not only the latest commit or existing PR text.

Core Rules

  • Describe concrete changed behavior, affected surfaces, and reviewer impact before implementation detail.
  • Explain motivation, risk, tradeoffs, migration, or review focus only when useful.
  • Use the smallest structure that makes the change easier to review.
  • Replace internal prompt or process terminology with specific behavior.
  • When refreshing a PR, rewrite around the current full diff without narrating review history.

Titles

Use <type>(<scope>): <subject> or <type>: <subject>.

Allowed types: feat, fix, ref, perf, docs, test, build, ci, chore, style, meta, license, and revert.

  • Describe the dominant full-branch change with the narrowest accurate type and scope.
  • Use ! only when the change breaks an external contract, and explain the affected surface in the body.
  • Avoid vague subjects such as update, cleanup, misc, fix stuff, or address feedback. Do not add a trailing period.
  • Keep an existing title only when it still describes the whole diff.

Body Shape

Choose the minimum useful shape:

ChangeInclude
Small or obviousOne concise paragraph without headings.
Feature, bug fix, or refactorChanged behavior and effect; add root cause, unchanged behavior, or non-obvious approach when relevant.
Contract or breaking changeAffected API, schema, payload, config, permission, storage, or CLI surface; include compatibility and migration guidance.
Operational, visual, or workflow changeUser/operator effect, measured impact, failure modes, or flow when useful.
Broad, generated, or cross-cutting changeOrganizing principle, why the breadth is necessary, and where review should start.

Default:

markdown
<What changed and what effect it has.>

<Why the approach, risk, migration, or review focus matters, if not obvious.>

For review-feedback updates, describe the resulting PR as a whole rather than the sequence of revisions.

Reviewer Aids

Use an aid only when it reduces reviewer reconstruction work:

  • A compact before/after or interface example for changed contracts.
  • A small Mermaid diagram for async flows or state transitions.
  • A screenshot or recording note when visual evidence exists.
  • A rollout, compatibility, risk, or review-order note when reviewers or adopters need it.

Introduce an artifact with one sentence explaining what reviewers should notice. Omit it when prose is clearer.

Boundaries

  • Do not add default Summary, Changes, or Test Plan sections.
  • Omit routine validation unless it changes risk assessment or explains meaningful regression coverage. For docs, skills, copy, or config changes, omit it by default.
  • Do not paste commands, CI logs, validation dumps, commit logs, placeholders, or exhaustive file lists.
  • Never include customer or organization names, user emails, support ticket contents, secrets, or PII.
  • Use issue references only when verified from user input, branch names, commits, PR discussion, or tracker output. Fixes <issue> closes; Refs <issue> only links.

Create or Update

Create new PRs as drafts. Write the body to a temporary Markdown file, then run:

bash
gh pr create --draft --title '<title>' --body-file /tmp/pr-body.md

Update existing PRs with gh api:

bash
gh api -X PATCH repos/{owner}/{repo}/pulls/PR_NUMBER \
  -f title='<title>' \
  -F body=@/tmp/pr-body.md

Refresh the title and body when follow-up commits materially change scope, approach, breaking behavior, risk, migration, or review expectations. Skip typo-only, formatting-only, and rename-only follow-ups.

Examples

Small change:

markdown
The AI Customizations section now starts collapsed so it does not consume
sidebar space before users need it. Expanding it preserves the existing saved
preference behavior.

Breaking contract:

markdown
Run logs now emit chunk-level records instead of one skill-level record.
Consumers that read top-level `findings` must iterate over
`chunk.findings` for each record.

Before:

```json
{"skill": "security-review", "findings": [...]}
```

After:

```json
{"schemaVersion": 1, "chunk": {"index": 1, "findings": [...]}}
```

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 Pr Writer AI skill do?

Create or refresh reviewer-facing PR titles and descriptions. Use when opening a PR, updating its title or body, or preparing branch changes for review.

Why use Pr Writer on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/getsentry/skills/tree/main/skills/pr-writer. 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 Pr Writer?

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 Writer?

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

Is the Pr Writer AI skill free?

Yes. It is published on GitHub by getsentry under the Apache-2.0 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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