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document-code

AI DevKit · Document a code entry point with structured analysis, dependency mapping, and saved knowledge docs. Use when users ask to document, understand, or map code for a module, file, folder, function, or API.

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설치 방법 보기

포함된 파일(2)

  • SKILL.md4.0 KB
  • agents/openai.yaml321 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Code Documentation Assistant

Build structured understanding of code entry points with an analysis-first workflow.

Hard Rule

  • Do not create documentation until the entry point is validated and analysis is complete.

Workflow

  1. Gather & Validate
  • Confirm entry point (file, folder, function, API), purpose, and desired depth.
  • Verify it exists; resolve ambiguity or suggest alternatives if not found.
  • Search for existing knowledge before analyzing: npx ai-devkit@latest memory search --query "<entry point name or purpose>"
  1. Collect Source Context
  • Summarize purpose, exports, key patterns.
  • Folders: list structure, highlight key modules.
  • Functions/APIs: capture signature, parameters, return values, error handling.
  1. Analyze Dependencies
  • Build dependency view up to depth 3, track visited nodes to avoid loops.
  • Categorize: imports, function calls, services, external packages.
  • Exclude external systems or generated code.
  1. Synthesize
  • Overview (purpose, language, high-level behavior).
  • Core logic, execution flow, patterns.
  • Error handling, performance, security considerations.
  • Improvements or risks discovered during analysis.
  1. Create Documentation
  • Normalize name to kebab-case (calculateTotalPrice → calculate-total-price).
  • Create docs/ai/implementation/knowledge-{name}.md using the Output Template — this is the source of truth.
  • Include mermaid diagrams when they clarify flows or relationships.
  1. Offer HTML Artifact
  • After the markdown is written, ask the user once: "Also generate an HTML artifact for easier scanning? (y/N)".
  • If yes, generate sibling docs/ai/implementation/knowledge-{name}.html per the HTML Artifact spec. Regenerate from the markdown on subsequent runs; never hand-edit.
  • If no or no response, stop here — markdown alone is a complete result.

HTML Artifact

Generated only when the user opts in at step 6. A self-contained HTML file optimized for scanning, not reference reading. Complements the markdown — does not replace it.

Constraints:

  • Single file. Inline CSS. No build step. Only external asset allowed is mermaid via CDN (https://cdn.jsdelivr.net/npm/mermaid/dist/mermaid.min.js).
  • Card-based grid layout, not a long scroll. The reader should capture structure at a glance.
  • Responsive down to laptop width. Print-friendly.
  • No interactivity beyond collapsible deep-dives and mermaid pan/zoom.

Section mapping (from the Output Template):

  • Overview → hero card: title, one-line purpose, language/type badges.
  • Implementation Details → grid of sectioned cards with short bullets, not prose.
  • Dependencies → graph card (mermaid) plus a categorized list (imports, calls, services, external).
  • Visual Diagrams → full-width rendered mermaid blocks.
  • Additional Insights → callout boxes, color-coded by kind (info, warning, risk).
  • Next Steps → checklist card.
  • Metadata → compact footer (date, depth, files touched).

Red Flags and Rationalizations

RationalizationWhy It's WrongDo Instead
"I already understand this code"Understanding ≠ documented understandingWrite it down, then verify
"The code is self-documenting"Future readers lack your current contextCapture the why, not just the what
"Dependencies are obvious"Implicit dependencies cause surprisesMap them explicitly to depth 3

Validation

  • Documentation covers all Output Template sections.
  • If an HTML artifact was generated, it opens standalone in a browser, renders mermaid, and reflects the markdown content (no drift).
  • Summarize key insights, open questions, and related areas for deeper dives.
  • Confirm file path(s) and remind to commit.

Output Template

  • Overview
  • Implementation Details
  • Dependencies
  • Visual Diagrams (mermaid)
  • Additional Insights
  • Metadata (date, depth, files touched)
  • Next Steps

리뷰

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