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infinite-gratitude

Multi-agent research that keeps bringing gifts back — like cats! Dispatch multiple agents to research a topic in parallel, compile findings, and iterate on new discoveries.

The English summary is being prepared. Showing the original description.

Works withHugging Face
See how to install

Files included (14)

  • SKILL.md2.3 KB
  • .gitattributes66 B
  • .gitignore3.6 KB
  • assets/demo-10-agents.png1.2 MB
  • assets/demo-10-cats-promotion.png1.2 MB
  • docs/hackernews_post.md1.3 KB
  • docs/producthunt_draft.md3.8 KB
  • docs/PROMOTION_LOG.md880 B
  • docs/README.ja.md5.1 KB
  • docs/README.zh.md4.1 KB
  • infinite-gratitude-story.md17.0 KB
  • LICENSE1.0 KB
  • README.md4.8 KB
  • references/agent-config.md1.5 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Infinite Gratitude 🐾

無限貓報恩 | 無限の恩返し Multi-agent research that keeps bringing gifts back — like cats! 🐱

Quick Reference

OptionValuesDefault
topicRequired-
--depthquick / normal / deepnormal
--agents1-105

Usage

/infinite-gratitude "pet AI recognition"
/infinite-gratitude "RAG best practices" --depth deep
/infinite-gratitude "React state management" --agents 3

Behavior

Step 1: Split Directions

Split {topic} into 5 parallel research directions:

  1. GitHub projects
  2. HuggingFace models
  3. Papers / articles
  4. Competitors
  5. Best practices

Step 2: Dispatch Agents

Task(
    prompt="Research {direction} for {topic}...",
    subagent_type="research-scout",
    model="haiku",
    run_in_background=True
)

Step 3: Collect Gifts

Compile all findings into structured report.

Step 4: Loop

If follow-up questions exist → Ask user → Continue? → Back to Step 2

Step 5: Final Report

Example Output

🐾 Infinite Gratitude!

📋 Topic: "pet AI recognition"
🐱 Dispatching 5 agents...

━━━━━━━━━━━━━━━━━━━━━━
🎁 Wave 1
━━━━━━━━━━━━━━━━━━━━━━

🐱 GitHub: MegaDescriptor, wildlife-datasets...
🐱 HuggingFace: DINOv2, CLIP...
🐱 Papers: Petnow uses Siamese Network...
🐱 Competitors: Petnow 99%...
🐱 Tutorials: ArcFace > Triplet Loss...

💡 Key: Data volume is everything!

🔍 New questions:
   - How to implement ArcFace?
   - How to use MegaDescriptor?

Continue? (y/n)

🐾 by washinmura.jp

Notes

  • Uses haiku model to save cost
  • Max 5 agents per wave
  • Deep mode loops until satisfied

Additional Resources

Related Skills

  • ai-dojo — Foundation for AI coding agents
  • research-scout — Single-agent research

Part of 🥋 AI Dojo Series by Washin Village 🐾

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