gemini-visualize

name	gemini-visualize
description	Generates interactive HTML visualizations (concept maps, evidence networks, knowledge graphs) from Gemini analysis results. Triggers automatically after /gr:video, /gr:research, /gr:analyze.

Gemini Visualize — Interactive Analysis Visualization

Generate a single-file interactive HTML visualization after every /gr:* analysis, then capture a Playwright screenshot. The agent decides enrichment depth autonomously but respects user steering ("skip visualization", "deeper on X").

Template Selection

Source Command	Template	Visualization Type
/gr:video, /gr:video-chat	video-concept-map	Concept map with knowledge states
/gr:research	research-evidence-net	Evidence network with tier filtering
/gr:analyze	content-knowledge-graph	Knowledge graph with entity types

Read the appropriate template from skills/gemini-visualize/templates/ before generating.

Core HTML Requirements

Every generated visualization MUST be a single self-contained HTML file with:

1. No external dependencies — all CSS, JS, SVG/Canvas inline
2. Dark theme — background #0a0a0f, nodes/text in light colors, high-contrast edges
3. Canvas or SVG rendering — prefer <canvas> for large graphs, <svg> for smaller ones
4. State object pattern — all app state in a single state = {...} object at the top of <script>
5. Responsive layout — works in both full-page browser and embedded views
6. Smooth animations — transitions on hover, click, filter changes (200-300ms)

Data Mapping (Agent Decisions)

The agent autonomously decides:

• Concept hierarchy depth — based on content richness (3-8 top-level nodes typical, 15-25 total with children)
• Which concepts become nodes vs. which are properties of nodes — major themes → nodes, supporting details → node metadata
• Relationship types — derived from context (e.g., "enables", "contradicts", "builds on", "example of")
• Initial knowledge states — default to unknown unless the user has indicated familiarity
• Category assignment — cluster nodes by topic/theme, assign colors per category

Visualization Features (All Templates)

Required

• Drag-and-drop nodes with physics-based layout (spring simulation or force-directed)
• Zoom and pan via mouse wheel and drag on background
• Node click — shows detail panel with description, source timestamp/citation, related nodes
• Category legend — clickable to filter nodes by category
• Search/filter — text input to highlight matching nodes
• Responsive sidebar — detail panel slides in from right, doesn't overlap graph on wide screens

Template-Specific

• Concept maps: Knowledge state cycling (Know → Fuzzy → Unknown → Know) on node click
• Evidence networks: Evidence tier filter (checkboxes per tier), source toggle
• Knowledge graphs: Entity type filter, importance threshold slider

Prompt Output Generation

Every visualization includes a "Generate Prompt" button that:

1. Reads the current state (selected nodes, knowledge states, filters)
2. Generates a focused learning/research prompt based on the user's selections
3. Copies it to clipboard with a toast notification

This lets users cycle knowledge states, then generate a targeted prompt to paste back into Claude.

Screenshot Workflow

After generating and saving the HTML file:

1. Start HTTP server: lsof -ti:18923 | xargs kill -9 2>/dev/null; python3 -m http.server 18923 --directory <artifact-dir> &
   • Use the specific artifact directory (e.g., gr/video/<slug>/)
   • Port 18923 — kill any prior instance first to avoid address-in-use errors
2. Navigate: mcp__playwright__browser_navigate to http://localhost:18923/<viz-filename>
   • concept-map.html for video/video-chat
   • evidence-net.html for research
   • knowledge-graph.html for analyze
3. Wait: mcp__playwright__browser_wait_for with 2-second timeout for canvas/SVG render
4. Screenshot: mcp__playwright__browser_take_screenshot — save raw bytes
5. Save PNG: Write screenshot data to <artifact-dir>/screenshot.png
6. Cleanup: Kill HTTP server process, mcp__playwright__browser_close

If Playwright fails (not installed, browser error), skip screenshot gracefully — the HTML visualization is the primary artifact. Log the failure but don't block the workflow.

Agent Autonomy & User Steering

Autonomous (no user input needed)

• Template selection based on source command
• Concept/node extraction from analysis results
• Relationship inference between concepts
• Category clustering
• Knowledge state defaults (all unknown)
• Screenshot capture

User can override

• "skip visualization" or "no viz" — suppress concept map generation entirely
• "deeper on X" — triggers enrichment of concept X with more detail nodes
• "simpler" — reduce node count, merge minor concepts into parent nodes
• "focus on X and Y" — filter visualization to show only selected concept clusters
• Cycling knowledge states in the playground and pasting the generated prompt back

File Organization

All artifacts for one analysis live together:

gr/<category>/<slug>/
├── analysis.md          # Progressive markdown (timestamped entries)
├── concept-map.html     # Interactive visualization (or evidence-net.html, knowledge-graph.html)
└── screenshot.png       # Playwright capture of the visualization