sstklen 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
| Option | Values | Default |
|---|---|---|
topic |
Required | - |
--depth |
quick / normal / deep | normal |
--agents |
1-10 | 5 |
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:
- GitHub projects
- HuggingFace models
- Papers / articles
- Competitors
- 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
haikumodel to save cost - Max 5 agents per wave
- Deep mode loops until satisfied
Additional Resources
- For agent configuration, see references/agent-config.md
Related Skills
- ai-dojo — Foundation for AI coding agents
- research-scout — Single-agent research
Part of 🥋 AI Dojo Series by Washin Village 🐾