docs-canvas/skills/docs-canvas/SKILL.md
Render a documentation-style Cursor Canvas that organizes architecture notes, API references, walkthroughs, and how-tos into a navigable layout with sections, tables of contents, and cross-references. Use when the user asks for a docs canvas, documentation overview, architecture walkthrough, API reference page, or wants to render structured documentation as an interactive canvas.
npx skillsauth add cursor/plugins docs-canvasInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Build a canvas that presents documentation — architecture notes, API references, design docs, runbooks, or codebase walkthroughs — as an interactive, navigable surface rather than as a flat markdown file.
Status: placeholder. The skill structure is in place so the canvas welcome page can surface this plugin via the marketplace query, but the full skill body still needs to be written. Treat the steps below as a starting outline and refine as the docs canvas pattern matures.
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.
Accept any of: a directory of markdown files, a single doc URL, an inline outline, or a question to answer from the codebase. Collect headings, code blocks, diagrams, and any cross-references between documents.
Decide the top-level structure before writing any components. A docs canvas usually has:
Prefer built-in canvas components over raw HTML:
Write reader-facing prose. Lead with the answer or the headline, then explain. Keep examples small and runnable. Cite source files with code references so readers can jump in.
The sections above are a floor, not a ceiling. The goal is the fastest possible path for the reader to understand the topic — so look at the source material in front of you and ask what representation would actually help. A diagram, a sequence chart, a side-by-side comparison, a decision tree, a glossary, a curated FAQ, a single large worked example — whatever fits.
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.