agentsclimarketplace

Image to mission

Skill Tibsfox/gsd-skill-creator/project-claude/skills/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.From its SKILL.md

Install
npx -y skills add Tibsfox/gsd-skill-creator --skill image-to-mission

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

SKILL.md

4.6 KB, 872 tokens by cl100k_base, as published. Nobody here has run it

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

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.