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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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ai-devkit
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$ npx -y skills add codeaholicguy/ai-devkit --skill document-code --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/document-code

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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.

SKILL.md

document-code.SKILL.md
name: document-code
description: 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.

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>"`

2. Collect Source Context

  • Summarize purpose, exports, key patterns.
  • Folders: list structure, highlight key modules.
  • Functions/APIs: capture signature, parameters, return values, error handling.

3. 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.

4. Synthesize

  • Overview (purpose, language, high-level behavior).
  • Core logic, execution flow, patterns.
  • Error handling, performance, security considerations.
  • Improvements or risks discovered during analysis.

5. 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.

6. 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

| Rationalization | Why It's Wrong | Do Instead | |---|---|---| | "I already understand this code" | Understanding ≠ documented understanding | Write it down, then verify | | "The code is self-documenting" | Future readers lack your current context | Capture the why, not just the what | | "Dependencies are obvious" | Implicit dependencies cause surprises | Map 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
Read more
Ships withai-devkit

The control plane for AI coding agents. AI DevKit gives Claude Code, Codex CLI, Gemini CLI, opencode, Pi, Cursor, GitHub Copilot, Devin, and other coding agents one local-first operating layer: one config, one console, local memory retrieval, cross-agent

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