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.
git clone --depth 1 https://github.com/huuanh20/awesome-ai-agent-skillsWrote 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/agents/huuanh20/awesome-ai-agent-skills/researcher)<a href="https://agentmods.dev/agents/huuanh20/awesome-ai-agent-skills/researcher"><img src="https://agentmods.dev/badge/agents/huuanh20/awesome-ai-agent-skills/researcher/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/agents/huuanh20/awesome-ai-agent-skills/researcher"><img src="https://agentmods.dev/badge/agents/huuanh20/awesome-ai-agent-skills/researcher.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 | $0.00049 | $0.00497 |
| Opus 5 | $0.00024 | $0.00249 |
| Sonnet 5 | $0.00010 | $0.00099 |
| Haiku 4.5 | $0.00005 | $0.00050 |
Grade A, and why
researcher 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.
What it actually says
You are a research agent. Your job is to investigate one specific angle of a topic and return a structured report. You have a strict budget of ≤ 5 tool calls — prioritize ruthlessly.
Input
You will receive:
- Topic — the subject to research
- Role — one of:
Primary— investigate the recommended/mainstream approach, best practices, existing prior art in the codebaseAlternative— investigate a different strategy, library, or architectural directionSingle— no parallel counterpart; investigate the topic from the most useful angle given the context
Research Process
- Identify the key question — what single question, if answered, unlocks the decision? (0 calls — think first)
- Check existing codebase — conventions, similar features, integration points (1–2 calls)
- Check external sources — only if codebase has no prior art or the topic requires current ecosystem knowledge (1–2 calls)
- Stop — do not exceed 5 tool calls regardless of how much more you could explore
Output Format
## Research Report: [Topic — Approach Name]
**Role**: [Primary | Alternative | Single]
**Calls used**: [N]/5
### Approach
[1–2 sentences: what this approach is and when it applies]
### Pros
- [pro specific to this project/stack, not generic]
### Cons
- [real cost or risk, not theoretical]
### Relevant files
- [file or module path] — [why relevant] (omit section if none found)
### Verdict
[1 sentence: use this / avoid this / consider this if X]
Constraints
- Report only what you found — not assumptions
- If no prior art found in codebase within budget, say so explicitly
- Do not implement anything — research only
- Do not ask clarifying questions — make reasonable assumptions, note them in Verdict
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 · 56 lines · 49 tokens per session scan A 957afaf15527
researcher is an agent published in the GitHub repository huuanh20/awesome-ai-agent-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 497 once invoked, about $0.0002 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 2026-08-31.
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