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image-to-mission

Extract creative intent from images into executable build specs. Activates on images + build intent, "image to mission", "i2m", or capturing visual energy in code/design.

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包含的文件(1)

  • SKILL.md4.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Image to Mission

Takes one or more images plus optional creator context and produces:

  1. Structured 4-layer visual analysis (literal, spatial, relational, mood)
  2. Extracted technical parameters (color, geometry, material, feel)
  3. Executable build instructions with philosophy annotations
  4. 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

FormatWhenContent
Direct buildSimple, single-medium outputCode/SVG + philosophy notes
Build specMedium complexityStep-by-step instructions
Mission packageComplex, multi-componentFull vision_to_mission handoff
Transmission packageCross-context workJSON/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

  1. Observe before building — spend time with images
  2. Process reveals pattern — ask how, not just what
  3. Emergent > designed — honor organic over mechanical
  4. Feel over fidelity — capture energy, not pixels
  5. 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

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