Initial commit: Clean DSS implementation
Migrated from design-system-swarm with fresh git history.
Old project history preserved in /home/overbits/apps/design-system-swarm
Core components:
- MCP Server (Python FastAPI with mcp 1.23.1)
- Claude Plugin (agents, commands, skills, strategies, hooks, core)
- DSS Backend (dss-mvp1 - token translation, Figma sync)
- Admin UI (Node.js/React)
- Server (Node.js/Express)
- Storybook integration (dss-mvp1/.storybook)
Self-contained configuration:
- All paths relative or use DSS_BASE_PATH=/home/overbits/dss
- PYTHONPATH configured for dss-mvp1 and dss-claude-plugin
- .env file with all configuration
- Claude plugin uses ${CLAUDE_PLUGIN_ROOT} for portability
Migration completed: $(date)
🤖 Clean migration with full functionality preserved
This commit is contained in:
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dss-claude-plugin/commands/dss-quick-wins.md
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dss-claude-plugin/commands/dss-quick-wins.md
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---
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name: dss-quick-wins
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description: Find quick win opportunities for design system adoption
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arguments:
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- name: path
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description: Path to project directory
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required: false
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---
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# DSS Quick Wins Command
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Find low-effort, high-impact opportunities for design system adoption.
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## Usage
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```
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/dss-quick-wins [path]
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```
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Examples:
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```
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/dss-quick-wins
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/dss-quick-wins ./src
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```
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## What This Does
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1. **Analyzes Codebase**
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- Scans styles and components
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- Identifies patterns
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- Measures usage frequency
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2. **Finds Opportunities**
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- Color consolidation
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- Spacing standardization
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- Typography cleanup
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- Border radius normalization
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- Shadow standardization
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3. **Scores by Impact/Effort**
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- Calculates potential impact
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- Estimates implementation effort
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- Ranks by ROI
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4. **Generates Recommendations**
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- Prioritized list
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- Specific actions
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- Expected outcomes
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## Instructions for Claude
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When the user runs this command:
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1. Use `dss_find_quick_wins` tool with path
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2. Present quick wins in priority order
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3. For each quick win, show:
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- Category (colors, spacing, etc.)
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- Impact level (high/medium/low)
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- Effort level (high/medium/low)
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- Specific values to consolidate
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- Files affected
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4. Provide total time estimate
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5. Offer to implement top quick wins
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## Example Output
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```
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Quick Win Analysis: /path/to/project
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TOP QUICK WINS
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1. COLOR CONSOLIDATION
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Impact: HIGH | Effort: LOW
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Found 47 color values reducible to 8 tokens
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Files affected: 23
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Consolidate:
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#0066cc, #0067cd, #0065cb -> primary
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#6c757d, #6b747c, #6d767e -> secondary
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Estimated time: 2 hours
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2. SPACING STANDARDIZATION
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Impact: HIGH | Effort: LOW
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Found 34 spacing values reducible to 6 tokens
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Files affected: 31
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Consolidate to 4px grid:
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4px, 8px, 16px, 24px, 32px, 48px
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Estimated time: 3 hours
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3. BORDER RADIUS NORMALIZATION
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Impact: MEDIUM | Effort: LOW
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Found 12 radius values reducible to 4 tokens
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Files affected: 15
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Consolidate:
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2px (sm), 4px (md), 8px (lg), 16px (xl)
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Estimated time: 1 hour
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4. SHADOW CLEANUP
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Impact: MEDIUM | Effort: LOW
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Found 8 shadow definitions reducible to 3 tokens
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Files affected: 12
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Consolidate:
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sm: 0 1px 2px rgba(0,0,0,0.05)
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md: 0 4px 6px rgba(0,0,0,0.1)
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lg: 0 10px 15px rgba(0,0,0,0.1)
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Estimated time: 1 hour
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5. FONT SIZE SCALE
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Impact: HIGH | Effort: MEDIUM
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Found 15 font sizes reducible to 7 tokens
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Files affected: 28
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Consolidate to type scale:
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12px, 14px, 16px, 18px, 24px, 32px, 48px
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Estimated time: 3 hours
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SUMMARY
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Total quick wins: 5
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Total estimated time: 10 hours
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Expected impact: 60% reduction in style inconsistency
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RECOMMENDED ORDER
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1. Colors (biggest impact)
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2. Spacing (most widespread)
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3. Border radius (quick win)
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4. Shadows (contained scope)
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5. Font sizes (needs coordination)
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Ready to implement? I can create tokens for any of these.
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```
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