MCP.Market

pr-report skill

by paperclipai·paperclipai/paperclip·114k stars·MIT

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.

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Is the pr-report skill safe?

Clean: nothing in its files matched our rules. We read 3 files in the folder on 2026-10-12.

No findings.

Install the pr-report skill

A skill is a folder. Copy it into your agent's skills folder and the agent loads it when the task matches its description.

git clone --depth 1 https://github.com/paperclipai/paperclip.git /tmp/paperclip
mkdir -p ~/.claude/skills
cp -r /tmp/paperclip/.agents/skills/pr-report ~/.claude/skills/pr-report
available in every project

In the Claude apps, zip the folder and upload it from the Skills settings. The folder on GitHub

The instructions your agent would load

SKILL.md as published, without the frontmatter. Read it on GitHub

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?

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

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