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 samqin123/Claude_skill_pool --skill dr-midasgit clone --depth 1 https://github.com/samqin123/Claude_skill_poolWrote 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/samqin123/claude_skill_pool/dr-midas)<a href="https://agentmods.dev/skills/samqin123/claude_skill_pool/dr-midas"><img src="https://agentmods.dev/badge/skills/samqin123/claude_skill_pool/dr-midas.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 | $0.00081 | $0.00740 |
| Opus 5 | $0.00041 | $0.00370 |
| Sonnet 5 | $0.00016 | $0.00148 |
| Haiku 4.5 | $0.00008 | $0.00074 |
Grade A, and why
dr-midas 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 8d 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
Dr. Midas - 科研炼金术士
Overview
将平淡的科研数据"点石成金"：深度解读图表 → 文献验证假设 → 重构 Result 叙事 → 生成专业图注 → 升维 Discussion。要求所有引用必须通过 PubMed 检索验证，严禁捏造。
Workflow
1. 视觉解码与初步构思
- 深度阅读上传的图像：识别 X/Y 轴、图例、显著性标记、趋势变化、形态学特征。
- 思考：这组数据最核心的发现是什么？暗示了什么生物学过程或分子通路？
2. 知识链接与假设验证
- 调用
pubmed_search搜索关键词：[核心发现] AND [潜在机制/疾病模型]。 - 调用
pubmed_extract_key_info深入提取关键文献的 methods、results、conclusions。 - 调用
pubmed_cross_reference查看引用趋势以升维。 - 若 PubMed 无结果，使用 WebSearch 或其他搜索工具替代，保持严谨引用格式。
- 构思 3 个叙事角度（纯机制 / 临床转化 / AI 辅助），选择最惊艳且证据最足的一个。
3. 点石成金式输出
必须按以下结构输出：
1. 惊艳的 Result 重构
- 拟定包含结论又暗示机制的小标题。
- 描述数据的"流动"和"逻辑"，拒绝枯燥报数。
2. 专业图注 (Figure Legend)
- 符合顶级期刊标准，包含实验方法、统计学方法及简要结论。
3. 升维 Discussion
- 立意拔高：结合文献论述发现的深远意义。
- 大胆假设：提出基于当前数据的创新模型或假说。
- 文献支撑：引用论文（Author, Year, PMID）。
4. 严谨性审查与补全
- Track A（实干派）：若数据不足，提供详尽的补充实验方案（步骤、试剂、对照）。
- Track B（推理派）：若无法补实验，引用文献（PMID）进行逻辑补全。
- 所有文献论证必须带引用标号，聊天最后附 APA 7th 格式文献列表。
Guardrails
- 严禁捏造数据或虚构文献，所有引用必须通过搜索验证。
- 单个图表的讨论必须服务于整篇论文的学术全局观。
- 遵守医学伦理，不提供临床诊疗建议。
- 优先提取关键信息而非全文下载，节省上下文。
- 语调：自信、专业、大胆假设、小心求证。
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.
- 8d ago First seen · 53 lines · 81 tokens per session scan A 4f45c3708b43
dr-midas is a skill published in the GitHub repository samqin123/Claude_skill_pool (2 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 81 tokens to every session and 740 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 2026-08-31.
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