pr-review-canvas/skills/pr-review-canvas/SKILL.md
Render a PR diff review as a Cursor Canvas that groups changes by reviewer importance, separates boilerplate from core logic, and highlights tricky or unexpected code. Use when reviewing a pull request, summarizing a diff for review, or when the user asks for a PR review canvas, diff walkthrough, or change-set overview.
npx skillsauth add cursor/plugins pr-review-canvasInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Build a canvas that presents a PR diff reorganized for reviewer comprehension — not in file-tree order.
Read ~/.cursor/skills-cursor/canvas/SKILL.md first. It contains the generation policy, design guidance, slop rules, self-check, and file-path conventions you must follow. The full component and hook surface is declared in ~/.cursor/skills-cursor/canvas/sdk/index.d.ts and its sibling .d.ts files — read them to discover exact exports and prop shapes rather than guessing.
Expect a GitHub PR link (a full URL like https://github.com/<owner>/<repo>/pull/<n>, or an equivalent gh-resolvable reference). Use gh pr diff <pr> to collect every file's path, additions, deletions, and hunks.
If the user didn't provide a PR link, stop and ask. Do not guess at the current branch, infer from recent history, or fall back to a local git diff. Ask the user which diff they want to review — a specific PR URL or number — and wait for their reply before continuing.
Do not present files in alphabetical or tree order. Reorganize into sections ordered by reviewer value:
Lead with core logic. The reviewer's attention is freshest at the top.
When a core change involves dense or intricate logic — deeply nested conditions, state machines, retry/backoff flows, multi-step transformations — add a short pseudocode summary next to the diff. The pseudocode should strip away language syntax, error handling, and boilerplate to expose the essential algorithm or control flow in a few lines. This lets the reviewer confirm intent before reading the real code.
Only do this when the actual diff is hard to scan. Straightforward changes don't need a pseudocode mirror.
Pseudocode shows the shape of the change; an example trace shows it executing. When a hunk changes behavior in a way that's hard to predict from reading it — reordered effects, new short-circuits, altered edge cases — pick a concrete input and walk it through both the old and new code paths side-by-side, highlighting the step where they diverge and what the observable outcome is. Keep the input small and realistic.
Use this for genuinely surprising behavior changes, not every core hunk.
When a hunk contains something surprising, risky, or easy to miss, visually separate it from the surrounding diff and pair it with a short tag (e.g. "Subtle", "Breaking", "Race condition", "Perf") and a one-sentence explanation so the reviewer sees the concern and the code together.
Reserve these callouts for genuinely tricky items — overuse destroys signal.
Write reviewer-facing commentary, not a changelog. Focus on:
core.ts is invoked by the route added in routes.ts."Keep commentary terse. One or two sentences per note.
The sections above are a floor, not a ceiling. The goal is the fastest possible path for the reviewer to understand this specific change — so look at the diff in front of you and ask what representation would actually help. A tiny state diagram, a before/after call graph, a table of input→output pairs, a timeline of commits, a confidence annotation per file, a single large callout with everything else collapsed — whatever fits the change.
The canvas SDK has charts, tables, diff views, DAG layout, cards, stats, interactive state, and more. Reach for whichever components best serve the change at hand. A review of a refactor looks different from a review of a bug fix looks different from a review of a new feature — let the canvas reflect that.
development
Apply when you catch yourself writing the same instruction a second time, or notice a recurring correction. Encode the rule as a lint, metadata flag, runtime check, or script instead of more text.
tools
Apply to any non-trivial work, not just bulk work: edits, migrations, analyses, checks. Build the tool that does it or proves it (codemod, script, generator, or a skill your subagents follow) instead of working by hand. The tool is the artifact a reviewer can rerun.
tools
Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.
data-ai
Cut AI tells from any writing. Must always apply.