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Get Started Free →Generate roadmap visualizations and planning artifacts for product planning
.claude/skills/a5c-ai-roadmap-visualization/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-07 | ✗→✓ | ▲ Improved | 70% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 370% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 90% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 53% | 0% |
| case-12 | ✗→✓ | ▲ Improved | -61% | 0% |
Specialized skill for generating roadmap visualizations and planning artifacts. Enables product teams to create clear, stakeholder-appropriate roadmap views in various formats.
This skill integrates with the following processes:
quarterly-roadmap.js - Primary roadmap planning and visualizationproduct-vision-strategy.js - Strategic roadmap viewsstakeholder-alignment.js - Stakeholder-specific roadmap presentationsproduct-council-review.js - Review-ready roadmap artifactsjson{ "type": "object", "properties": { "viewType": { "type": "string", "enum": ["now-next-later", "timeline", "gantt", "dependency", "resource"], "description": "Type of roadmap view to generate" }, "initiatives": { "type": "array", "items": { "type": "object", "properties": { "id": { "type": "string" }, "name": { "type": "string" }, "theme": { "type": "string" }, "timeframe": { "type": "string" }, "priority": { "type": "string" }, "dependencies": { "type": "array", "items": { "type": "string" } }, "team": { "type": "string" }, "confidence": { "type": "string", "enum": ["high", "medium", "low"] } } } }, "timeHorizon": { "type": "string", "description": "Time range for roadmap (e.g., 'Q1-Q4 2026')" }, "audience": { "type": "string", "enum": ["executive", "engineering", "sales", "customer", "internal"], "description": "Target audience for roadmap view" }, "outputFormat": { "type": "string", "enum": ["markdown", "mermaid", "csv", "json", "ascii"], "default": "markdown" } }, "required": ["viewType", "initiatives"] }
json{ "type": "object", "properties": { "visualization": { "type": "string", "description": "Rendered roadmap in requested format" }, "summary": { "type": "object", "properties": { "totalInitiatives": { "type": "number" }, "byTimeframe": { "type": "object" }, "byTheme": { "type": "object" }, "byPriority": { "type": "object" } } }, "dependencies": { "type": "array", "items": { "type": "object", "properties": { "from": { "type": "string" }, "to": { "type": "string" }, "type": { "type": "string" } } } }, "riskFlags": { "type": "array", "items": { "type": "string" }, "description": "Potential scheduling or dependency risks" } } }
javascriptconst roadmap = await executeSkill('roadmap-viz', { viewType: 'now-next-later', initiatives: [ { id: 'init-1', name: 'Core Platform Upgrade', theme: 'Platform', timeframe: 'now', priority: 'P0' }, { id: 'init-2', name: 'Mobile App Launch', theme: 'Growth', timeframe: 'next', priority: 'P1' }, { id: 'init-3', name: 'AI Features', theme: 'Innovation', timeframe: 'later', priority: 'P2' } ], timeHorizon: 'Q1-Q4 2026', audience: 'executive', outputFormat: 'markdown' });
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 14,976 | 24,474 | +63% | 1 | 1 | 0% | 2,723 | 4,015 | +47% | 0 | 0 | — |
case-02 | fail→fail | 9,782 | 8,465 | -13% | 1 | 1 | 0% | 2,027 | 2,929 | +44% | 0 | 0 | — |
case-03 | fail→fail | 10,603 | 11,290 | +6% | 1 | 1 | 0% | 2,288 | 3,305 | +44% | 0 | 0 | — |
case-04 | fail→fail | 6,850 | 6,668 | -3% | 1 | 1 | 0% | 1,386 | 2,472 | +78% | 0 | 0 | — |
case-05 | fail→fail | 6,844 | 6,352 | -7% | 1 | 1 | 0% | 1,437 | 2,502 | +74% | 0 | 0 | — |
case-06 | fail→fail | 26,552 | 15,654 | -41% | 1 | 1 | 0% | 5,586 | 3,599 | -36% | 0 | 0 | — |
case-07 | fail→pass | 7,197 | 7,818 | +9% | 1 | 1 | 0% | 1,579 | 2,688 | +70% | 0 | 0 | — |
case-08 | fail→pass | 3,151 | 6,858 | +118% | 1 | 1 | 0% | 582 | 2,737 | +370% | 0 | 0 | — |
case-09 | fail→pass | 7,609 | 9,130 | +20% | 1 | 1 | 0% | 1,654 | 3,138 | +90% | 0 | 0 | — |
case-10 | fail→fail | 15,491 | 11,945 | -23% | 1 | 1 | 0% | 2,779 | 3,386 | +22% | 0 | 0 | — |
case-11 | fail→pass | 10,446 | 7,924 | -24% | 1 | 1 | 0% | 1,791 | 2,740 | +53% | 0 | 0 | — |
case-12 | fail→pass | 34,161 | 10,288 | -70% | 1 | 1 | 0% | 8,238 | 3,219 | -61% | 0 | 0 | — |
case-13 | fail→pass | 31,889 | 12,421 | -61% | 1 | 1 | 0% | 6,603 | 3,427 | -48% | 0 | 0 | — |
case-14 | pass→pass | 12,434 | 9,940 | -20% | 1 | 1 | 0% | 1,922 | 3,228 | +68% | 0 | 0 | — |
case-15 | fail→fail | 15,138 | 6,091 | -60% | 1 | 1 | 0% | 3,061 | 2,482 | -19% | 0 | 0 | — |
case-16 | fail→fail | 13,793 | 11,905 | -14% | 1 | 1 | 0% | 2,400 | 3,295 | +37% | 0 | 0 | — |
case-17 | fail→pass | 11,729 | 11,313 | -4% | 1 | 1 | 0% | 1,883 | 3,017 | +60% | 0 | 0 | — |
case-18 | fail→pass | 7,542 | 7,406 | -2% | 1 | 1 | 0% | 1,225 | 2,346 | +92% | 0 | 0 | — |
case-19 | pass→pass | 8,804 | 11,111 | +26% | 1 | 1 | 0% | 1,868 | 3,012 | +61% | 0 | 0 | — |
case-20 | pass→pass | 30,720 | 31,827 | +4% | 1 | 1 | 0% | 4,753 | 6,391 | +34% | 0 | 0 | — |
case-21 | pass→pass | 11,313 | 19,757 | +75% | 1 | 1 | 0% | 2,277 | 4,216 | +85% | 0 | 0 | — |
case-22 | pass→pass | 19,295 | 26,918 | +40% | 1 | 1 | 0% | 3,339 | 5,548 | +66% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.