name: infinite-gratitude description: Multi-agent research that keeps bringing gifts back โ like cats! Dispatch multiple agents to research a topic in parallel, compile findings, and iterate on new discoveries. argument-hint: "<topic>" [--depth quick|normal|deep] [--agents 1-10]
Infinite Gratitude ๐พ
็ก้่ฒๅ ฑๆฉ | ็ก้ใฎๆฉ่ฟใ Multi-agent research that keeps bringing gifts back โ like cats! ๐ฑ
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 โ Ask user โ Continue? โ Back to Step 2
Step 5: Final Report
Example Output
๐พ Infinite Gratitude!
๐ Topic: "pet AI recognition"
๐ฑ Dispatching 5 agents...
โโโโโโโโโโโโโโโโโโโโโโ
๐ Wave 1
โโโโโโโโโโโโโโโโโโโโโโ
๐ฑ GitHub: MegaDescriptor, wildlife-datasets...
๐ฑ HuggingFace: DINOv2, CLIP...
๐ฑ Papers: Petnow uses Siamese Network...
๐ฑ Competitors: Petnow 99%...
๐ฑ Tutorials: ArcFace > Triplet Loss...
๐ก Key: Data volume is everything!
๐ New questions:
- How to implement ArcFace?
- How to use MegaDescriptor?
Continue? (y/n)
๐พ 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 โ Foundation for AI coding agents
- research-scout โ Single-agent research
Part of ๐ฅ AI Dojo Series by Washin Village ๐พ
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