Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add KaimingWan/oh-my-kiro --skill omk-researchgit clone --depth 1 https://github.com/KaimingWan/oh-my-kiroWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/kaimingwan/oh-my-kiro/omk-research)<a href="https://agentmods.dev/skills/kaimingwan/oh-my-kiro/omk-research"><img src="https://agentmods.dev/badge/skills/kaimingwan/oh-my-kiro/omk-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/kaimingwan/oh-my-kiro/omk-research"><img src="https://agentmods.dev/badge/skills/kaimingwan/oh-my-kiro/omk-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.00852 |
| Opus 5 | $0.00036 | $0.00426 |
| Sonnet 5 | $0.00015 | $0.00170 |
| Haiku 4.5 | $0.00007 | $0.00085 |
Grade A, and why
omk-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trigger Examples
- "@research AutoMQ vs Confluent 对比"
- "帮我调研一下这个库怎么用"
- "find out how competitors handle this"
- "what's the best practice for X in 2026?"
- "compare these three approaches"
Research Skill — Multi-Level Search
Search Level Strategy
Always use the lowest level that can answer the question:
| Level | Tool | Use Case | Cost |
|---|---|---|---|
| 0 | Built-in knowledge | Common concepts, basics | Free |
| 1 | web_search |
Quick verification, simple queries | Free |
| 2 | Tavily Research API | Deep research, competitive analysis | API credits |
Rule: If Level 0 or 1 can answer it, don't use Level 2.
Don't need research: Common knowledge, already in knowledge/, answerable from built-in knowledge.
Level 2: Tavily Research API
Prerequisites
Get your API key at https://tavily.com (1000 free credits/month)
Set environment variable:
export TAVILY_API_KEY="tvly-your-key-here"
Or add to your agent config:
{
"env": {
"TAVILY_API_KEY": "tvly-your-key-here"
}
}
Usage
./scripts/research.sh '{"input": "your research query"}' [output_file]
# Quick research
./scripts/research.sh '{"input": "quantum computing trends"}'
# Deep research
./scripts/research.sh '{"input": "AI agents comparison", "model": "pro"}'
# Save to file
./scripts/research.sh '{"input": "market analysis", "model": "pro"}' ./report.md
Model Selection
| Model | Use Case | Speed |
|---|---|---|
mini |
Single topic, targeted | ~30s |
pro |
Multi-angle, comprehensive | ~60-120s |
auto |
API chooses based on complexity | Varies |
Rule of thumb: "what does X do?" → mini. "X vs Y vs Z" → pro.
Structured Output
./scripts/research.sh '{
"input": "fintech startups 2025",
"model": "pro",
"output_schema": {
"properties": {
"summary": {"type": "string", "description": "Executive summary"},
"companies": {"type": "array", "items": {"type": "string"}}
},
"required": ["summary"]
}
}'
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 113 lines · 73 tokens per session scan A deb69c24fd86
omk-research is a skill published in the GitHub repository KaimingWan/oh-my-kiro (103 stars, last pushed 5mo ago), licensed MIT. It adds 73 tokens to every session and 852 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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