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.
Install
$ agentstack add skill-sstklen-infinite-gratitude-infinite-gratitude ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-sstklen-infinite-gratitude-infinite-gratitude) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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 3Behavior
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.jpNotes
- 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](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 🐾
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: sstklen
- Source: sstklen/infinite-gratitude
- License: MIT
- Homepage: https://washinmura.jp
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.