Image to Mission
SkillMediaExtract creative intent from images into executable build specs. Activates on images + build intent, "image to mission", "i2m", or capturing visual energy in code/design.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Image to Mission skill
What this skill tells your AI
The instructions your AI receives, as published by tibsfox/gsd-skill-creator in project-claude/skills/image-to-mission/SKILL.md and read by ahel’s review.
Takes one or more images plus optional creator context and produces:
- Structured 4-layer visual analysis (literal, spatial, relational, mood)
- Extracted technical parameters (color, geometry, material, feel)
- Executable build instructions with philosophy annotations
- Self-contained transmission package for cross-context handoff
When to Activate
Activate when the user provides images AND expresses intent to:
- Build, create, or make something based on the images
- Translate visual reference into code, design, or specifications
- Capture the "feel" or "energy" of images in another medium
- Create a mission package from visual reference
- Direct keywords: "image to mission", "i2m"
- Target medium: "translate this to [canvas/react/three.js/SVG/CSS]"
DO NOT activate when the user:
- Simply asks "what's in this image?" (use standard image analysis)
- Wants image editing or manipulation
- Needs OCR or text extraction from images
- Is asking about image file formats or metadata
- Asks to describe colors or content without build intent
Observation Protocol
Before building anything, enter observation mode:
Phase 1: Observe (mandatory — do not skip)
Process each image through four layers:
- Literal: Inventory all visible objects, materials, colors
- Spatial: Map relationships, arrangements, density
- Relational: Find patterns across images, note changes vs. constants
- Mood: Quantify atmosphere (energy, intimacy, order, handmade, ceremony)
Phase 2: Listen (if creator provides context)
Structure context into: process, intent, constraints, accidents, multipurpose. Extract the process insight — the key understanding about HOW it was made.
Phase 3: Connect
Synthesize observations + context into unified understanding. Find what neither source reveals alone.
Phase 4: Extract
Convert understanding to numerical parameters:
- Colors (palette, temperature, contrast, relationships)
- Geometry (shape, arrangement, symmetry, constants)
- Materials (surfaces, light interaction, blend modes)
- Feel (energy, intimacy, order, handmade, ceremony — all 0-1)
Phase 5: Build
Translate parameters to target medium. Generate step-by-step instructions with philosophy notes.
Phase 6: Document
Package everything for transmission. Validate self-containment.
Output Formats
| Format | When | Content |
|---|---|---|
| Direct build | Simple, single-medium output | Code/SVG + philosophy notes |
| Build spec | Medium complexity | Step-by-step instructions |
| Mission package | Complex, multi-component | Full vision_to_mission handoff |
| Transmission package | Cross-context work | JSON/Markdown bundle |
Implementation
Code lives in src/vtm/image-to-mission/. Key modules:
- observation-engine — four-layer observation (literal/spatial/relational/mood)
- context-integrator — freeform text parser, layer mapping, process insight extraction
- connection-engine — cross-image linker, visual-context bridge, synthesis orchestrator
- parameter-extractor — color/geometry/material/feel extraction with reference tables
- translation-code — Canvas, React/JSX, Three.js, CSS translators
- translation-design — SVG, palette, markdown layout spec
- build-generator — ordered atomic build steps with philosophy annotations
- transmission-packager — 5 self-containment checks, JSON + markdown serialization
- pipeline-bridge — complexity scoring (0-12), routing, override detection, v2m handoff
Key Principles
- Observe before building — spend time with images
- Process reveals pattern — ask how, not just what
- Emergent > designed — honor organic over mechanical
- Feel over fidelity — capture energy, not pixels
- Document for transmission — write for the next mind
Safety
- Output is inspired by, not a copy of, source images
- Creator context is attributed, never silently absorbed
- Simple description requests are rejected to avoid wasting observation protocol
Signals
- GitHub stars
- 69
- Forks
- 9
- Last commit
- Jul 2026
Advanced
- Catalog kind
- skill
- Gateway key
image-to-mission- Source
- github.com/tibsfox/gsd-skill-creator