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Agent skill

PR

by jellydn in jellydn/my-ai-tools

Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis.

MITAuto-check passedDevelopment

Install PR

skills CLI
$ npx skills add jellydn/my-ai-tools --skill pr -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jellydn/my-ai-tools pr --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jellydn/my-ai-tools.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/pr .claude/skills/pr && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pr
GitHub stars
123
Token cost
~1.4k tokens
SKILL.md length
605 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
MIT

At a glance

Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis.

  • Works in 3 steps: Use the draft-pull-request workflow to… → Verify the returned PR URL, title, base,… → Report the exact validation results and…
  • Tasks that involve Pull requests
  • SKILL.md covers When to Use, Required Inputs, Body Template and Publication, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

PR is an agent skill from jellydn/my-ai-tools. Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: cline, claude, opencode, amp, codex, gemini, cursor, pi

It sits in Development, covering Pull requests and Infographics. The repository describes itself as: Comprehensive configuration management for AI coding tools - Replicate my complete setup for Claude Code, OpenCode, Amp, Li, Codex and Claude Code Switch with custom… The licence is MIT.

When your agent uses it

  • Tasks that involve Pull requests
  • Tasks that involve Infographics

Example prompts

  • “/pr”

Requirements

  • Compatibility (from SKILL.md): cline, claude, opencode, amp, codex, gemini, cursor, pi

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Use the draft-pull-request workflow to create or update the PR with --body-file.
  2. Verify the returned PR URL, title, base, head, and draft state.
  3. Report the exact validation results and any environment-only blockers.

What it can do on your machine

Read from SKILL.md and the folder at commit 62c9227. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    cline, claude, opencode, amp, codex, gemini, cursor, pi

    From compatibility in the SKILL.md frontmatter.

Context cost

PR loads about 1.4k tokens when it runs. Until then it costs about 29 tokens; SKILL.md has 605 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~29
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jellydn/my-ai-tools at commit 62c9227, republished under its MIT licence (© jellydn). 605 words, ~1,435 tokens.

Download SKILL.mdSave it as .claude/skills/pr/SKILL.md (or your agent's skills folder).
name
pr
description
Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis.
compatibility
cline, claude, opencode, amp, codex, gemini, cursor, pi
version
1.0.0
author
my-ai-tools
license
MIT
hint
Use when preparing or updating a pull request for human review.
metadata.audience
all
metadata.workflow
git
metadata.related_skills
draft-pull-request, code-review, commit-atomic

Reviewable Pull Request

Prepare a pull request body that lets a human understand the change quickly, verify that it works, and spend review time where risk is highest. This skill improves the review narrative; it does not replace code review or validation.

When to Use

Use when:

  • A branch has a meaningful diff and needs a new or updated PR body.
  • The reviewer needs the shape of a refactor, flow, or integration explained.
  • The change has evidence and rollback implications worth making explicit.

Load draft-pull-request for repository preflight, branch handling, and gh publication rules. Reuse an existing PR instead of opening a duplicate.

Required Inputs

Before writing, gather:

  • The authoritative spec, issue, plan, or ticket graph.
  • The complete diff against the PR base.
  • The actual commands run and their output.
  • Any screenshots, logs, or before/after behavior available.
  • If a skill or workflow changed, the original input plus the pre-edit and post-edit outputs.
  • The current PR template and existing reviewer notes.

Never claim a test, screenshot, or manual check that was not actually run.

Body Template

Use these sections unless the repository's template requires equivalent headings:

markdown
## Summary

<the smallest visual that explains the change>

## Evidence

- **Before:** <failing test, old output, old screenshot, or baseline behavior>
- **After:** <passing test, new output, new screenshot, or verified behavior>

## Merge Danger

**Door:** <two-way or one-way>

**Blast Radius:** <one-word scope>

<what can break, what rollback restores, and where careful review matters>
Summary: show the shape

Choose one small visual, not a prose dump:

  • Call tree for runtime control flow.
  • Component tree for UI changes.
  • File tree for ownership or layout changes.
  • Diff sketch for a focused behavior change.
  • Mermaid sequence or flow for cross-component data movement.
  • Pseudocode for an algorithm or state transition.

Example:

text
implement-spec
  read spec + ticket graph
  frontier -> isolated workers
    ticket implementation + tests
  merge verified commits
  code-review integration branch

Keep only the files, calls, states, and boundaries needed to understand the change. Use the domain terms from GLOSSARY.md when the repository has one.

Evidence: before and after

Evidence should be execution-based whenever possible:

markdown
- **Before:** `pytest tests/test_export.py::test_csv` — failed: endpoint missing
- **After:** `pytest tests/test_export.py::test_csv` — passed
- **Full check:** `pytest -q` — 142 passed

For visual work, prefer screenshots. For bug fixes, show the original reproduction and the regression check. If there is no meaningful before state, say so and provide the strongest available verification instead of manufacturing one.

For skill changes, show the learning loop rather than only the edited Markdown:

markdown
- **Input:** <stable task or fixture>
- **Before:** <output from the previous skill>
- **Human edit:** <decision the user made and why>
- **After:** <output after updating the skill>
- **Rerun:** <same input compared against the intended result>

Prefer a decision rule with boundaries over a literal preference. If the lesson can be checked mechanically, include the lint/test/hook that now enforces it.

Show full SKILL.md (261 more words)Show less
Merge Danger: risk, not drama

Classify the door:

  • Two-way: reverting the commit restores the prior state without external cleanup.
  • One-way: it changes external state, data, contracts, migrations, messages, or other effects that a revert cannot fully undo.

Name the blast radius plainly: single-command, one-service, shared-library, data, all-users, or another accurate scope. Mention rollback steps, migration order, compatibility concerns, and the most important review seam.

Publication

After writing and checking the body:

  1. Use the draft-pull-request workflow to create or update the PR with --body-file.
  2. Verify the returned PR URL, title, base, head, and draft state.
  3. Report the exact validation results and any environment-only blockers.

Common Pitfalls

  1. Writing a paragraph where a small diagram would make the change obvious.
  2. Listing tests without showing the relevant before/after result.
  3. Saying “low risk” without identifying reversibility or blast radius.
  4. Treating a revert as complete rollback for a migration or external side effect.
  5. Describing intended behavior instead of the behavior actually verified.
  6. Replacing repository-specific PR headings or checked items without reading its template.
  7. Opening a second PR for a branch that already has one.

Verification Checklist

  • Spec, issue, or ticket source was read.
  • Diff was reviewed against the correct base.
  • Summary contains one useful visual or diff sketch.
  • Evidence includes real before/after results, or the limitation is explicit.
  • Skill changes include a same-input learning-loop result, when applicable.
  • Door type and blast radius are named.
  • Rollback and compatibility concerns are documented.
  • Repository PR template and existing reviewer notes were preserved.
  • PR metadata and URL were verified after publication.

© jellydn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/pr of jellydn/my-ai-tools.

Open the folder on GitHubat commit 62c9227

Compare with similar skills

PR next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

PR compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
PR this skilljellydn/my-ai-tools123—~1.4kAutomated safety check: PassMIT
Finishing a Development Branchobra/superpowers297k5 repos~1.9kAutomated safety check: PassMIT
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Check PRonyx-dot-app/onyx32k2 repos~2.3kAutomated safety check: PassMIT
PR Design DocOpenHands/OpenHands90k—~2.4kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence

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    Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.

    297k GitHub starsUsed in 5 repos~1.9k tokens
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  • PR Babysitter

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  • Capability Experiments

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  • PR Review

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Categories

Questions about PR

What does PR do?

Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis. PR is an agent skill from jellydn/my-ai-tools. Write a fast-to-review pull request body with a visual summary, before/after evidence, and merge-risk analysis.

When should I use PR?

PR fits situations like: tasks that involve Pull requests; tasks that involve Infographics.

How do I install PR in Claude Code?

Run `npx skills add jellydn/my-ai-tools --skill pr -a claude-code`. Or copy the skill folder (skills/pr in jellydn/my-ai-tools) into .claude/skills/pr in your project. Claude Code loads it when a task matches its description.

How do I install PR in Codex?

Run `npx skills add jellydn/my-ai-tools --skill pr -a codex`. Or copy the skill folder (skills/pr in jellydn/my-ai-tools) into .agents/skills/pr in your project. Codex loads it when a task matches its description.

Can I use PR in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jellydn/my-ai-tools --skill pr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pr, .gemini/skills/pr, .github/skills/pr and .opencode/skills/pr in your project.

What does PR need to run?

SKILL.md names no scripts, command-line tools or credentials: PR is instructions for the agent only. Compatibility (from SKILL.md): cline, claude, opencode, amp, codex, gemini, cursor, pi.

Does PR access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is PR safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does PR use?

PR is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does PR use?

About 1.4k tokens (SKILL.md is roughly 5.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to PR?

Skills that share tags, products or a category with PR: Finishing a Development Branch (obra/superpowers, 297k stars), PR Babysitter (openinterpreter/openinterpreter, 69k stars), Check PR (onyx-dot-app/onyx, 32k stars) and PR Design Doc (OpenHands/OpenHands, 90k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains PR?

jellydn (a GitHub user) maintains it in jellydn/my-ai-tools, which has 123 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 9, 2026.

Source: jellydn/my-ai-tools on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.