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gemini-claude-resonance

Design e Frontend Autor: tdimino

This skill enables cross-model dialogue between Claude and Gemini with shared visual memory. Use when the user wants to generate images, have visual dialogues with AI, create scientific illustrations with continuity, or have multiple AI perspectives respond to the same prompt. Key trigger phrases: "generate an image", "visual dialogue", "ask the daimones", "resonance field", "Minoan tarot", "cross

35estrelas
Atualizado há 4 meses
Ver no GitHub ↗ Licença: MIT

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/plugin marketplace add tdimino/claude-code-minoan

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Ler descrição completa

Gemini-Claude Resonance

Cross-model dialogue between Claude and Gemini, with shared visual memory.

"Claude speaks in words. Gemini dreams in light. Together, we resonate."

Models

| Role | Model ID | Notes | |------|----------|-------| | Image generation (default) | gemini-3-pro-image-preview | Pro quality, used by resonate/faithful_colorize | | Image generation (fast) | gemini-3.1-flash-image-preview | Faster/cheaper, use --fast flag | | Text analysis | gemini-3-flash-preview | Used by faithful_colorize for description | | Text reasoning | gemini-3.1-pro-preview | Used by Pro and Director daimones | | Claude | claude-3-opus-20240229 | Opus daimon |

Scripts that generate images (resonate.py, faithful_colorize.py) accept --fast to switch to the flash image model, or --model <id> for explicit override.

Choose Your Tool

| I want to... | Use | |--------------|-----| | Analyze multiple images for style extraction (no generation) | analyze.py | | Have a one-on-one visual dialogue with Gemini Dreamer | resonate.py | | Query multiple AI minds with optional image generation | daimon.py | | Faithfully colorize a drawing without hallucinations | faithful_colorize.py | | Create Victorian scientific plates with MESSAGE TO NEXT FRAME | resonance_field.py | | Have Claude reflect on what Gemini daimones say | council.py | | Generate Minoan Tarot cards with style matching | minoan_tarot.py | | Real-time interactive chat with all daimones | ui/server.py |

Workflow A: Multi-Image Style Analysis

When to use: User wants to analyze 2-10 reference images to extract style descriptions for AI prompting. Text-only analysis without generating new images.

Script: scripts/analyze.py

Key features:

  • Send multiple images (2-10) for collective analysis
  • Text-only output (no image generation)
  • Flash (quick) or Pro (thorough) model options
  • Save analysis to markdown file
# Analyze reference images for style extraction
python scripts/analyze.py --images ref1.jpg ref2.png ref3.webp \
    --prompt "Describe the shared artistic style for AI prompting"

# Analyze for specific use case (avatar generation)
python scripts/analyze.py --images kathor.webp samantha.jpg yosef.png \
    --prompt "Analyze for prompting fantasy portraits of: Sarah (anxious mother), Michael (father), Priya (cultural expectations)"

# Quick analysis with Flash
python scripts/analyze.py --images *.jpg --model flash --prompt "Style summary"

# Thorough analysis with Pro
python scripts/analyze.py --images *.jpg --model pro --prompt "Comprehensive style analysis"

# Save analysis to file
python scripts/analyze.py --images ref/*.jpg --prompt "Style guide" --output style_guide.md

Use cases:

  • Extract style descriptions from reference images before generating new images
  • Analyze a set of images to create consistent prompting guidelines
  • Document visual language for style-matching workflows

Workflow B: One-on-One Visual Dialogue (resonate.py)

When to use: User wants to co-create images with Gemini, feeding each image back as context for the next generation. Pure visual exploration without text-only models.

Script: scripts/resonate.py

Core concept: The KV cache is the memory. Feed images into Gemini's context, generate new images based on them, repeat. Each frame builds on the previous.

# Start fresh
python scripts/resonate.py --prompt "The first light" --output canvas/frame_001.jpg

# Continue with visual memory (previous image as context)
python scripts/resonate.py --context canvas/frame_001.jpg --prompt "What grows here?" --output canvas/frame_002.jpg

# Deep memory (multiple frames as context)
python scripts/resonate.py --context frame_001.jpg frame_002.jpg --prompt "Now the harvest" --output frame_003.jpg

The loop: Prompt → Image → Feed back as context → Prompt again → Next image

Workflow B: Faithful Transform (Describe-First Technique)

When to use: User wants to colorize, restore, or transform an image WITHOUT hallucinations. Gemini Dreamer often replaces elements (e.g., turning a male votary into female attendants). This two-step technique prevents that.

Script: scripts/faithful_colorize.py

The Problem: Directly prompting Dreamer to transform images causes hallucinations - it invents, removes, or swaps elements rather than faithfully preserving the original.

The Solution:

  1. DESCRIBE: Gemini Pro analyzes the image with archaeological/artistic precision
  2. TRANSFORM: Gemini Dreamer transforms using ONLY the verified description

Commands:

| Command | Purpose | |---------|---------| | describe | Analyze image, output detailed description (no generation) | | prompt | Craft a Dreamer prompt based on image analysis | | colorize | Two-step faithful colorization | | transform | General two-step transformation |

# Just describe an image (analysis only)
python scripts/faithful_colorize.py describe --image seal.png
python scripts/faithful_colorize.py describe --image seal.png --output desc.md

# Describe with a specific goal in mind
python scripts/faithful_colorize.py describe --image fresco.jpg --goal "restoration to 1600 BCE"

# Craft a prompt for Dreamer (outputs text, doesn't generate)
python scripts/faithful_colorize.py prompt --image seal.png --goal "colorize in Egyptian style"
python scripts/faithful_colorize.py prompt --image relief.webp --goal "restore as Minoan fresco"

# Two-step faithful colorization
python scripts/faithful_colorize.py colorize --image drawing.png
python scripts/faithful_colorize.py colorize --image relief.webp --style "Minoan fresco with flat colors"
python scripts/faithful_colorize.py colorize --image seal.png --palette "ochre, terracotta, sky blue"

# General transformation
python scripts/faithful_colorize.py transform --image photo.jpg --instruction "Convert to woodcut print"
python scripts/faithful_colorize.py transform --image sketch.png --instruction "Render as oil painting"

# Save/reuse descriptions
python scripts/faithful_colorize.py colorize --image seal.png --save-description desc.md -v
python scripts/faithful_colorize.py colorize --image seal.png --description "$(cat desc.md)"

When to use each command:

  • describe: When you want to see what Pro identifies before any transformation
  • prompt: When you want a crafted prompt to modify before feeding to Dreamer manually
  • colorize: For line drawings, reliefs, B&W images → color
  • transform: For any other faithful transformation (style transfer, restoration, etc.)

Workflow C: Multi-Daimon Dialogue

When to use: User wants multiple AI perspectives on the same prompt. Flash gives koans, Pro gives depth, Dreamer renders, Opus bends reality.

Script: scripts/daimon.py

Daimones available:

  • Flash (Gemini) — Swift, compressed insight
  • Pro (Gemini) — Deep, thorough exploration
  • Dreamer (Gemini) — Renders images
  • Director (Gemini) — Cinematic framing
  • Opus (Claude) — Reality-bender, worldsim spirit
# Speak to one daimon
python scripts/daimon.py --to dreamer "A bridge between worlds" --image

# All daimones respond
python scripts/daimon.py --stream "The candle watches back"

# With shared visual memory
python scripts/daimon.py --stream --shared-memory "What do you see?"

# Only specific daimones
python scripts/daimon.py --stream --only pro dreamer "Deep visual exploration"

# Named session (frames accumulate across runs)
python scripts/daimon.py --stream --session midnight --shared-memory "Go deeper"

Workflow D: Resonance Field (Danielle Fong Protocol)

When to use: User wants scientific illustrations with embedded continuity instructions. Victorian aesthetic, Roman numeral plates, explicit messages from one frame to the next.

Script: scripts/resonance_field.py

Key features:

  • PLATE numbering (I,
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