scan-design-system

name	scan-design-system
version	2.0.0
description	[Documentation] Use when scanning design tokens, component inventory, and app-to-doc design system mappings.

Quick Summary

Goal: Scan project for design system artifacts → populate docs/project-reference/design-system/README.md with overview, app-to-documentation mapping, design token inventory, and component catalog. (read directly when relevant; do not rely on hook-injected conversation text)

Workflow:

1. Classify — Detect design system type and approach before scanning
2. Scan — Parallel sub-agents discover structure, components, tokens
3. Report — Write findings incrementally to report file
4. Generate — Build/update reference doc from report
5. Fresh-Eyes — Round 2 verification validates paths and token values

Key Rules:

• Generic — works with any design system approach
• Discover organization dynamically from file system MUST ATTENTION detect design system TYPE first — agent emphasis depends on type
• Every reference must point to real files — NEVER fabricate component names or token values

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Scan Design System

Phase 0: Classify Design System Type

Before any other step, run in parallel:

1. Read docs/project-reference/design-system/README.md

   • Detect mode: Init (placeholder) or Sync (populated)
   • In Sync mode: extract section list → skip re-scanning well-documented sections

2. Detect design system type:

Signal	Type	Agent Emphasis
Token files (design-tokens.json, tokens.scss, Style Dictionary config)	Token-first	Prioritize Agent 3 (token discovery)
Storybook config (.storybook/, *.stories.ts)	Component-library	Prioritize Agent 2 (component inventory)
Figma token exports or figma-tokens.json	Figma-driven	Prioritize Agent 3 (token import chain)
Only component directories, no token files	Ad-hoc/CSS-only	Prioritize Agent 1 (structure)
Mix of above	Hybrid	Run all 3 agents with equal weight

3. Resolve config-driven paths from docs/project-config.json:

   • designSystem.canonicalDoc — single source of truth for new code
   • designSystem.tokenFiles — drop-in token files
   • Never hardcode these names — content varies per project, names come from config.

4. Check for app-specific design docs in the same directory

Evidence gate: Confidence <60% on design system type → report uncertainty, proceed with Agent 1 (structure) only.

Phase 1: Plan

Create TaskCreate entries for each sub-agent and each verification step. Do not start Phase 2 without tasks created.

Phase 2: Execute Scan (Parallel Sub-Agents)

Launch 3 general-purpose sub-agents in parallel. Each MUST:

• Write findings incrementally after each category — NEVER batch at end
• Cite file:line for every finding
• Confidence: >80% document; 60-80% note as "observed (unverified)"; <60% omit

All findings → plans/reports/scan-design-system-{YYMMDD}-{HHMM}-report.md

Agent 1: Design System Structure

Think: How is the design system organized? What's the canonical doc? What's the token chain? Which apps have design docs and which don't?

• Glob for docs/project-reference/design-system/** to map all design docs
• Find design token files (CSS custom properties, SCSS variables, JSON tokens)
• Discover Storybook stories (*.stories.ts, *.stories.tsx, *.stories.mdx)
• Find component library entry points (index files, barrel exports)
• Map app-to-design-doc relationships
• Verify canonical doc at {docsPath}/{canonicalDoc} has expected sections. Flag missing sections.
• Verify token files at {docsPath}/{tokenFiles[i]} exist and contain variable declarations. Flag empty/missing.

Agent 2: Component Inventory

Think: What dimensions define a complete component inventory? Consider: Discoverability (can I find it?), Categorization (what type?), Variant coverage (size/color/state?), Accessibility (ARIA/keyboard?), Documentation completeness (JSDoc/README/Storybook?), Icon/asset library coverage.

For each dimension, derive the specific grep/glob patterns from what the project actually uses — do NOT hardcode Angular/React/Vue-specific patterns unless confirmed.

• Find reusable UI components (shared component directories, exported components)
• Find component categories (layout, forms, feedback, navigation, data display)
• Discover component variants (size, color, state variations)
• Find icon sets or asset libraries
• Look for accessibility patterns (ARIA roles, keyboard support)
• Find documentation for individual components

Agent 3: Token & Component Source Discovery

Think: What design tokens actually exist in source code (not just what's documented)? Which are declarations (authoritative) vs usages (derived)?

Source scope (whitelist, not full repo):

• src/**/styles/**/*.{scss,css}, src/**/themes/**/*.{scss,css}, src/**/tokens/**/*.{scss,css}
• src/**/*.scss ONLY when path contains theme, token, palette, design, style-guide, or variables
• Exclude node_modules, dist, .nx, coverage, component-local styles

Discovery rules (declarations only, NOT usages):

• CSS custom properties (declarations): --[a-zA-Z][a-zA-Z0-9_-]*\s*: — capture LHS only, dedupe
• SCSS variable declarations: ^\s*\$[a-zA-Z][a-zA-Z0-9_-]*\s*: — anchor to start-of-line
• Color values used ≥3 times across whitelist (hex, rgb, hsl)
• Spacing scale (declarations): (padding|margin|gap)\s*:\s*[\d.]+(px|rem|em) — extract values, dedupe
• Typography (declarations): (font-family|font-size|font-weight)\s*: — extract RHS, dedupe
• Breakpoints: @media[^{]*\((min|max)-width:\s*[\d.]+(px|em|rem)\) — extract widths, dedupe

Categorise: Colors / Typography / Spacing / Breakpoints / Z-Index / Elevation / Component-prefixes / Other. Persist incrementally — append to report after each category. Quality gate: If a category has <3 unique entries OR >200 entries, log "scope too narrow/broad — manual refinement required".

Phase 3: Analyze & Generate

Read report. Build target sections.

Round 1 (main agent): Build section drafts from report findings.

Round 2 (fresh sub-agent, zero memory): Independently verifies:

• All doc paths exist on filesystem (Glob check — not just "looks right")
• All token values are from actual declarations, not usages or fabricated
• Component names in inventory match actual files (Grep check)
• Gap Analysis section present (what's missing, not just what exists)

Target Sections

Section	Content
Design System Overview	High-level description — type, tools, organization
App Documentation Map	Table: App name, Design doc path, Token source, Component library
Design Tokens	Token categories, file locations, naming convention — values from declarations
Component Inventory	Table: Component name, Category, Variants, Path, Has docs?
Gap Analysis	Missing docs, zero-adoption tokens, undocumented components
Icon & Asset Library	Icon set source, asset directory paths, usage patterns
Storybook	Setup (if exists), story organization, how to add new stories
Usage Guidelines	How to consume tokens and components in application code

Authoring (init mode only)

When init mode detected (canonical doc missing or placeholder):

1. Author {docsPath}/{canonicalDoc} from Agent 3 findings:
   • Prepend regen marker: <!-- Generated by /scan-design-system on YYYY-MM-DD; refine sections manually -->
   • Sections: Foundations, Tokens, Components, Patterns, Accessibility, Adoption Strategy
2. Author each {docsPath}/{tokenFiles[i]} from grouped declarations:
   • First: REMOVE PLACEHOLDER_MARKER_SCSS sentinel before writing real tokens
   • .scss: SCSS variable block per category + CSS custom property mirrors in :root {}
   • Categories: Colors, Typography, Spacing, Breakpoints, Z-Index, Elevation/Shadow
3. Preserve manual content in sync mode — DO NOT overwrite populated doc/token file

Phase 4: Write & Verify

1. Write updated doc with <!-- Last scanned: YYYY-MM-DD --> at top
2. Surgical update only — preserve unchanged sections
3. Verify config-driven paths: {docsPath}/{canonicalDoc} and every {docsPath}/{tokenFiles[i]}
4. Verify (Glob): ALL component paths in inventory exist — not just 3
5. Verify (Grep): Token names in doc match actual declarations in source
6. Verify: Gap Analysis section present
7. Report: sections updated / unchanged / gaps documented / canonical + token presence

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[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks per file read. Prevents context loss from long files. Simple tasks: ask user whether to skip.

Prerequisites: MUST ATTENTION READ before executing:

Critical Thinking Mindset — Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources, admit uncertainty, self-check output, cross-reference independently. Certainty without evidence = root of all hallucination.

Scan & Update Reference Doc — Surgical updates only, NEVER full rewrite.

1. Read existing doc first — understand structure and manual annotations
2. Detect mode: Placeholder (headings only) → Init. Has content → Sync.
3. Scan codebase (grep/glob) for current patterns
4. Diff findings vs doc — identify stale sections only
5. Update ONLY diverged sections. Preserve manual annotations.
6. Update metadata (date, version) in frontmatter/header
7. NEVER rewrite entire doc. NEVER remove sections without evidence obsolete.

Output Quality — Token efficiency without sacrificing quality.

1. No inventories/counts — stale instantly
2. No directory trees — use 1-line path conventions
3. No TOCs — AI reads linearly
4. One example per pattern — only if non-obvious
5. Lead with answer, not reasoning
6. Sacrifice grammar for concision in reports
7. Unresolved questions at end

AI Mistake Prevention — Failure modes to avoid:

Verify AI-generated content against actual code. AI hallucinates component names/token values. Grep to confirm existence before documenting. NEVER invent variable values, hex colors, or mixin signatures. Grep to confirm before documenting. Trace full dependency chain after edits. Always trace full chain. Surface ambiguity before coding. NEVER pick silently.

IMPORTANT MUST ATTENTION read existing doc first, scan codebase, diff, surgical update only. Never rewrite entire doc.

IMPORTANT MUST ATTENTION output quality: no counts/trees/TOCs, 1 example per pattern, lead with answer.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small TaskCreate tasks BEFORE starting IMPORTANT MUST ATTENTION detect design system TYPE in Phase 0 — agent emphasis depends on it IMPORTANT MUST ATTENTION NEVER invent variable values, hex colors, or mixin signatures — Grep to confirm IMPORTANT MUST ATTENTION sub-agents write findings incrementally after each category — NEVER batch at end IMPORTANT MUST ATTENTION Gap Analysis section is mandatory — document what's missing, not just what exists IMPORTANT MUST ATTENTION when Round 1 finds issues, Round 2 fresh-eyes after fixing validates paths and token values. Clean Round 1 ENDS the scan.

Anti-Rationalization:

Evasion	Rebuttal
"Design system type obvious, skip Phase 0 detection"	Phase 0 is BLOCKING — agent emphasis depends on detected type
"Only 2 agents needed, skip token discovery agent"	Token discovery is separate from component inventory — NEVER merge
"Token values look correct"	Grep-verify ALL token values against declarations — "looks correct" ≠ verified
"Gap Analysis not needed"	Gap Analysis is a required section — documents what's missing for future work
"Skip Round 2 even when Round 1 found issues"	Clean Round 1 (zero issues) does end the scan. But when issues exist, fresh-eyes is mandatory after fixing — main agent rationalizes own mistakes.
"Verified 3 paths, that's enough"	Glob-verify ALL paths in inventory — spot-check is insufficient

[TASK-PLANNING] Before acting, analyze task scope and break into small todo tasks and sub-tasks using TaskCreate.