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 MerkyorLynn/Lynn --skill deep-researchgit clone --depth 1 https://github.com/MerkyorLynn/LynnWrote 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/merkyorlynn/lynn/deep-research)<a href="https://agentmods.dev/skills/merkyorlynn/lynn/deep-research"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/deep-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/merkyorlynn/lynn/deep-research"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00460 |
| Opus 5 | $0.00019 | $0.00230 |
| Sonnet 5 | $0.00008 | $0.00092 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
deep-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 9d 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
Deep Research 深度研究技能
当用户请求深度研究、调研分析、信息整理时，按以下流程执行：
研究流程
第 1 步：理解需求
- 明确研究主题和用户关注的重点
- 确定需要回答的核心问题（3-5 个）
第 2 步：广度搜索（至少 3 次搜索）
- 使用
web_search搜索主题的不同维度 - 搜索 1：主题 + 最新动态/新闻
- 搜索 2：主题 + 深度分析/专业观点
- 搜索 3：主题 + 数据/统计/对比
第 3 步：深度阅读（至少读取 2-3 个网页）
- 使用
web_fetch读取搜索结果中最有价值的页面 - 提取关键数据、观点、引用
第 4 步：交叉验证
- 对比不同来源的信息是否一致
- 标注存在争议或不确定的信息
- 补充搜索解决信息缺口
第 5 步：综合输出
- 将研究成果整理为结构化报告
- 使用
create_artifact生成 HTML 报告（如果内容丰富） - 或使用
create_report生成专业报告（如果是股票/行业分析） - 标注所有信息来源
输出规范
- 每个事实都标注来源
- 区分"已确认事实"和"分析推测"
- 给出明确的结论和建议
- 如果是对比分析，使用表格呈现
适用场景
- "帮我调研一下 XXX"
- "深度分析 XXX 的前景"
- "对比 A 和 B 的优劣"
- "整理 XXX 的最新进展"
- "研究一下 XXX 市场"
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.
- 9d ago First seen · 50 lines · 39 tokens per session scan A 59e0c60d08d0
deep-research is a skill published in the GitHub repository MerkyorLynn/Lynn (42 stars, last pushed yesterday), licensed Apache-2.0. It adds 39 tokens to every session and 460 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 2026-08-30.
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