common-skills: Skill for Claude Code

PR Walkthrough

Create a local static HTML/CSS/JavaScript walkthrough that orients a reviewer to the current branch's pull request as four separate interactive D3 views. The walkthrough should help the reviewer understand the affected code and the PR from four distinct views:

• System overview view: a concise standalone code overview for the subsystem touched by the PR. It should not feel like a graph. Present it as a small set of expanded component cards that give the reviewer just enough architectural context to get their bearings before reviewing the PR. Do not mention the PR, changed files, review comments, diff links, screenshots, specs, or implementation deltas in this view.
• Data flow graph: how state, data, events, requests, files, assets, or rendered output move through the changed system.
• Code dependency graph: which changed components depend on each other, where the major seams are, and which files are entry points versus leaf dependencies.
• User action graph: what the user does, what surface they interact with, and how that action flows through the implementation. This skill is an experiment in canvas-based PR comprehension. Do not reproduce the slideshow format. Do not put all perspectives on one graph. Generate four separate canvas views that the user can toggle between, and provide a guided tour within each view so the site teaches the PR from start to finish. Scale the walkthrough to the PR size: a small PR should feel like a compact reviewer aid, not a comprehensive architecture document. This skill is not a code-review skill. Do not generate new review findings, approve/request-changes recommendations, or exhaustive critique. Use the full codebase at the PR/head commit, the PR diff, PR description, specs changed by the PR, and existing review comments from humans or agents to produce orientation maps that help a reviewer understand the change quickly.

Output

Create a self-contained site at:

• .warp/pr-walkthrough/index.html The site must be loadable directly from the local filesystem with a file:// URL. Do not require a dev server, package install, bundler, or build step. Prefer one self-contained HTML file with inline CSS, inline JavaScript, and inline data. If splitting files is unavoidable, use only relative local files and avoid fetch() because browser restrictions can block local file reads. D3 should be loaded from a pinned official release on a reputable CDN. Use the helper script's default unless there is a concrete reason to change it:
• https://cdn.jsdelivr.net/npm/[email protected]/dist/d3.min.js Do not use unpinned latest URLs, unofficial builds, or dynamic package ranges. Do not show repeated D3 implementation disclaimers in the UI. Keep CDN/runtime details in validation logs or final caveats only when relevant. For reusable deterministic D3 rendering, prefer the helper script at scripts/d3_canvas_runtime.py. It emits Brandalf-aligned CSS, an inline runtime loader that defines the renderer before injecting the pinned D3 script, and a graph renderer with zoom, pan, graph switching, search, node details, fit-to-view, and guided tour controls. Use this helper rather than writing one-off D3 setup code in each generated walkthrough. The generated canvas must be treated as generated code that requires validation. Before reporting that a walkthrough is ready, run scripts/validate_d3_canvas.py against the generated HTML. If the canvas fails to initialize, D3 fails to load, required graphs are missing, tour controls do not work, nodes/edges do not render, or browser validation cannot be performed in an environment where it should be available, debug and regenerate before saying the walkthrough is ready. If a browser-capable environment is genuinely unavailable, report canvas rendering as unverified instead of ready.