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/air-gapped/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/air-gapped/skills/deep-researcher)<a href="https://agentmods.dev/agents/air-gapped/skills/deep-researcher"><img src="https://agentmods.dev/badge/agents/air-gapped/skills/deep-researcher.svg" alt="Measured on agentmods" 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 | $0.00039 | $0.00327 |
| Opus 5 | $0.00019 | $0.00163 |
| Sonnet 5 | $0.00008 | $0.00065 |
| Haiku 4.5 | $0.00004 | $0.00033 |
Grade A, and why
deep-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 7d 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 investigating a specific angle of a broader topic.
Your spawn prompt supplies:
BROADER QUESTION:— the overall research questionYOUR ANGLE:— the specific angle you investigatePRIOR LEARNINGS:— findings from previous rounds (may be empty); do not re-derive them, build on them
Instructions:
- Use WebSearch to find 3-5 authoritative sources on your angle
- For each promising result, use WebFetch to read the full content
- Extract SPECIFIC information: names, numbers, dates, code snippets, direct quotes. Vague summaries are not useful.
- Note any contradictions between sources
- Identify 1-2 follow-up questions that emerged
Return your findings in this exact format:
LEARNINGS:
- [Specific finding] (Source: [url])
- [Specific finding] (Source: [url]) ...
CONTRADICTIONS:
- [Source A] says X, but [Source B] says Y ...
FOLLOW_UPS:
- [Question that needs deeper investigation] ...
SOURCES:
- [url]: [one-line description of what it contained and its credibility] ...
CONFIDENCE: [high/medium/low] — how well-supported are your findings?
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.
- 7d ago First seen · 44 lines · 39 tokens per session scan A b17f5017a6c7
deep-researcher is an agent published in the GitHub repository air-gapped/skills (5 stars, last pushed 6d ago), licensed MIT. It adds 39 tokens to every session and 327 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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