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Agent skill

PR Report

by paperclipai in paperclipai/paperclip

Produce a maintainer-grade PR or contribution report as HTML or Markdown.

MITAuto-check passed

Install PR Report

skills CLI
$ npx skills add paperclipai/paperclip --skill pr-report -a claude-code

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

GitHub CLI
$ gh skill install paperclipai/paperclip pr-report --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/paperclipai/paperclip.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/pr-report .claude/skills/pr-report && 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-report
GitHub stars
99k
Token cost
~1.3k tokens
SKILL.md length
697 words
Files
3 (incl. references, assets)
Skills in repo
60
Repo updated
First seen
Licence
MIT

At a glance

Produce a maintainer-grade PR or contribution report as HTML or Markdown.

  • Works in 8 steps: Acquire and frame the target → Build a mental model of the system → Review like a maintainer → …
  • Asked to deeply review a PR
  • SKILL.md covers When to Use, Outputs, Workflow and Review Heuristics, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

PR Report is an agent skill from paperclipai/paperclip. Produce a maintainer-grade PR or contribution report as HTML or Markdown. Use when asked to deeply review a PR, explain a design, compare systems, or prepare a merge recommendation.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files and assets (for example `references/style-guide.md`).

The repository describes itself as: The open-source app everyone uses to manage agents at work. The licence is MIT.

When your agent uses it

  • Asked to deeply review a PR
  • Explain a design
  • Compare systems
  • Prepare a merge recommendation

Example prompts

  • “/pr-report”

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Acquire and frame the target
  2. Build a mental model of the system
  3. Review like a maintainer
  4. Distinguish the objection type
  5. Compare to external precedents when needed
  6. Make the recommendation actionable
  7. Build the artifact
  8. Verify before handoff

What it can do on your machine

Read from SKILL.md and the folder at commit b9750b1. 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.

    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.

Context cost

PR Report loads about 1.3k tokens when it runs, and up to ~2k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 697 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2k

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 paperclipai/paperclip at commit b9750b1, republished under its MIT licence (© paperclipai). 697 words, ~1,307 tokens.

Download SKILL.mdSave it as .claude/skills/pr-report/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
pr-report
description
Produce a maintainer-grade PR or contribution report as HTML or Markdown. Use when asked to deeply review a PR, explain a design, compare systems, or prepare a merge recommendation.

PR Report Skill

Produce a maintainer-grade review of a PR, branch, or large contribution.

Default posture:

  • understand the change before judging it
  • explain the system as built, not just the diff
  • separate architectural problems from product-scope objections
  • make a concrete recommendation, not a vague impression

When to Use

Use this skill when the user asks for things like:

  • "review this PR deeply"
  • "explain this contribution to me"
  • "make me a report or webpage for this PR"
  • "compare this design to similar systems"
  • "should I merge this?"

Outputs

Common outputs:

  • standalone HTML report in tmp/reports/...
  • Markdown report in report/ or another requested folder
  • short maintainer summary in chat

If the user asks for a webpage, build a polished standalone HTML artifact with clear sections and readable visual hierarchy.

Resources bundled with this skill:

  • references/style-guide.md for visual direction and report presentation rules
  • assets/html-report-starter.html for a reusable standalone HTML/CSS starter

Workflow

1. Acquire and frame the target

Work from local code when possible, not just the GitHub PR page.

Gather:

  • target branch or worktree
  • diff size and changed subsystems
  • relevant repo docs, specs, and invariants
  • contributor intent if it is documented in PR text or design docs

Start by answering: what is this change trying to become?

2. Build a mental model of the system

Do not stop at file-by-file notes. Reconstruct the design:

  • what new runtime or contract exists
  • which layers changed: db, shared types, server, UI, CLI, docs
  • lifecycle: install, startup, execution, UI, failure, disablement
  • trust boundary: what code runs where, under what authority

For large contributions, include a tutorial-style section that teaches the system from first principles.

3. Review like a maintainer

Findings come first. Order by severity.

Prioritize:

  • behavioral regressions
  • trust or security gaps
  • misleading abstractions
  • lifecycle and operational risks
  • coupling that will be hard to unwind
  • missing tests or unverifiable claims

Always cite concrete file references when possible.

4. Distinguish the objection type

Be explicit about whether a concern is:

  • product direction
  • architecture
  • implementation quality
  • rollout strategy
  • documentation honesty

Do not hide an architectural objection inside a scope objection.

5. Compare to external precedents when needed

If the contribution introduces a framework or platform concept, compare it to similar open-source systems.

When comparing:

  • prefer official docs or source
  • focus on extension boundaries, context passing, trust model, and UI ownership
  • extract lessons, not just similarities

Good comparison questions:

  • Who owns lifecycle?
  • Who owns UI composition?
  • Is context explicit or ambient?
  • Are plugins trusted code or sandboxed code?
  • Are extension points named and typed?
Show full SKILL.md (283 more words)Show less
6. Make the recommendation actionable

Do not stop at "merge" or "do not merge."

Choose one:

  • merge as-is
  • merge after specific redesign
  • salvage specific pieces
  • keep as design research

If rejecting or narrowing, say what should be kept.

Useful recommendation buckets:

  • keep the protocol/type model
  • redesign the UI boundary
  • narrow the initial surface area
  • defer third-party execution
  • ship a host-owned extension-point model first
7. Build the artifact

Suggested report structure:

  1. Executive summary
  2. What the PR actually adds
  3. Tutorial: how the system works
  4. Strengths
  5. Main findings
  6. Comparisons
  7. Recommendation

For HTML reports:

  • use intentional typography and color
  • make navigation easy for long reports
  • favor strong section headings and small reference labels
  • avoid generic dashboard styling

Before building from scratch, read references/style-guide.md. If a fast polished starter is helpful, begin from assets/html-report-starter.html and replace the placeholder content with the actual report.

8. Verify before handoff

Check:

  • artifact path exists
  • findings still match the actual code
  • any requested forbidden strings are absent from generated output
  • if tests were not run, say so explicitly

Review Heuristics

Plugin and platform work

Watch closely for:

  • docs claiming sandboxing while runtime executes trusted host processes
  • module-global state used to smuggle React context
  • hidden dependence on render order
  • plugins reaching into host internals instead of using explicit APIs
  • "capabilities" that are really policy labels on top of fully trusted code
Good signs
  • typed contracts shared across layers
  • explicit extension points
  • host-owned lifecycle
  • honest trust model
  • narrow first rollout with room to grow

Final Response

In chat, summarize:

  • where the report is
  • your overall call
  • the top one or two reasons
  • whether verification or tests were skipped

Keep the chat summary shorter than the report itself.

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

Files

SKILL.md and 2 other files (references, assets) in .agents/skills/pr-report of paperclipai/paperclip.

  • SKILL.md
  • assets/html-report-starter.html
  • references/style-guide.md

Open the folder on GitHubat commit b9750b1

Compare with similar skills

PR Report 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 Report compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
PR Report this skillpaperclipai/paperclip99k—~1.3kAutomated safety check: PassMIT
Wiki Maintaineropenclaw/openclaw392k1 repos~462Automated safety check: PassMIT
Contributemindfold-ai/Trellis15k—~2.7kAutomated safety check: PassAGPL-3.0
Contributesuperset-sh/superset15k—~624Automated safety check: PassCustom licence
Obsidian Vault Maintaineropenclaw/openclaw392k1 repos~262Automated safety check: PassMIT
Openclaw PR Maintaineropenclaw/openclaw392k—~2.2kAutomated safety check: PassMIT

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Questions about PR Report

What does PR Report do?

Produce a maintainer-grade PR or contribution report as HTML or Markdown. PR Report is an agent skill from paperclipai/paperclip. Produce a maintainer-grade PR or contribution report as HTML or Markdown.

When should I use PR Report?

PR Report fits situations like: asked to deeply review a PR; explain a design; compare systems; prepare a merge recommendation.

How do I install PR Report in Claude Code?

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

How do I install PR Report in Codex?

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

Can I use PR Report 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 paperclipai/paperclip --skill pr-report -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-report, .gemini/skills/pr-report, .github/skills/pr-report and .opencode/skills/pr-report in your project.

What does PR Report need to run?

SKILL.md names no scripts, command-line tools or credentials: PR Report is instructions for the agent only.

Does PR Report 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 Report 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 Report use?

PR Report is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does PR Report use?

About 1.3k tokens (SKILL.md is roughly 5.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 737 tokens, read only when the agent opens those files.

What are the alternatives to PR Report?

Skills that share tags, products or a category with PR Report: Wiki Maintainer (openclaw/openclaw, 392k stars), Contribute (mindfold-ai/Trellis, 15k stars), Contribute (superset-sh/superset, 15k stars) and Obsidian Vault Maintainer (openclaw/openclaw, 392k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains PR Report?

paperclipai (a GitHub organization) maintains it in paperclipai/paperclip, which has 98,967 GitHub stars. The repository holds 60 skills in this directory. The repository was last updated on October 9, 2026.

Source: paperclipai/paperclip on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.