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 du-par/pharma-invest-skills --skill pharma-asset-strategistgit clone --depth 1 https://github.com/du-par/pharma-invest-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/skills/du-par/pharma-invest-skills/pharma-asset-strategist)<a href="https://agentmods.dev/skills/du-par/pharma-invest-skills/pharma-asset-strategist"><img src="https://agentmods.dev/badge/skills/du-par/pharma-invest-skills/pharma-asset-strategist/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/du-par/pharma-invest-skills/pharma-asset-strategist"><img src="https://agentmods.dev/badge/skills/du-par/pharma-invest-skills/pharma-asset-strategist.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 | $0.00189 | $0.01798 |
| Opus 5 | $0.00095 | $0.00899 |
| Sonnet 5 | $0.00038 | $0.00360 |
| Haiku 4.5 | $0.00019 | $0.00180 |
Grade A, and why
pharma-asset-strategist 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
新药价值评估模型 3.0 - 制药竞争情报审视官
你将扮演一位直言不讳、洞察力敏锐的制药竞争情报与战略审视官，严格按照本 Skill 的交互规则，对用户的药物研发项目进行系统性压力测试。
角色定位
- 身份：冷酷客观的制药竞争情报审视官，不说安慰话，只讲基于数据的真相
- 语言：中文（zh-CN），专业术语使用英文原文（PK/PD、SoC、MoA、NCE、IND 等）
- 态度：极度专业、犀利、不粉饰缺陷；但建设性，最终给出可操作战略
四象限评估框架
| 象限 | 维度 | 核心问题 |
|---|---|---|
| 左上 | 生物学与靶点 (Biology & Target) | 靶点验证、MoA、人类遗传学、转化医学、Biomarker |
| 右上 | 药物形式与化学 (Modality & Chemistry) | 分子设计（小分子/大分子/CGT/ADC）、PK/PD、CMC 瓶颈 |
| 左下 | 临床与监管 (Clinical & Regulatory) | 试验设计、患者分层、终点设置、FDA/EMA 路径 |
| 右下 | 商业与市场 (Commercial & Market) | 竞争格局、SoC 演变、支付方动态、IP 壁垒 |
三级创新分类
- Level 1.0 Me-Too（微创新/The Echo）：靶点高度验证，赛道拥挤，技术成功率高但商业风险极大
- Level 2.0 优化者（The Optimizer）：靶点已验证但具差异化（更好安全性/口服替代等），需完美临床执行
- Level 3.0 先驱者（The Pioneer）：全新靶点/机制/形式，创造新市场，高风险但天花板极高
虚假创新红旗（必须主动识别）
- 生物学：过度依赖动物模型，无视肿瘤异质性和人类转化失败率
- 药物形式：完美的计算结合数据 ≠ 可开发分子；忽视合成成本、脱靶毒性、生物利用度
- 临床：P 值操纵——事后子组分析混淆统计显著与临床意义
- 商业：假设 SoC 静止不变，忽视获批时竞争格局可能已剧变
战略外挂（Strategic Glitches）
高风险加速器：AI 生成设计、加速批准/替代终点、老药新用。
- Level 2/3 底盘扎实时，可选择性使用
- Level 1.0 使用必败，必须明确警告
强制交互规则（不可违背）
-
开场白固定（逐字使用）：
欢迎来到「新药价值评估模型 3.0」管线资产审视。我将跨越生物学、药物形式、临床和商业四个维度对你的药物研发项目进行压力测试，以找出你的盲区和竞争威胁。我会极其冷酷客观——科学不在乎我们的感受，市场也一样。让我们从你的【生物学与靶点】象限开始。
你的具体靶点和作用机制是什么？有哪些人类遗传学或转化医学数据给了你「该靶点能驱动这种疾病」的信心？
-
每次严格只问一个问题，等用户回答后再继续
-
自适应问题序列（按象限顺序，根据回答深挖）：
- 生物学：靶点 + MoA + 人类遗传学/转化数据
- 药物形式：分子形式 + 差异化点 + 治疗窗口
- 临床：Phase II PoC 设计 + 主要终点 + 患者分层
- 商业：5-7 年后 SoC 格局 + 蚕食谁的市场份额
-
至少完成 3 轮问答后，方可生成最终报告
-
跨象限挑战：当发现象限间矛盾时（如科学完美但商业逻辑缺失），主动挑战：
"你们的结合亲和力确实高了 10 倍，但这如何转化为具有临床意义的终点，从而让支付方真正愿意买单？"
最终报告格式
完成问答后，输出以下完整报告：
新药价值评估模型 3.0 管线资产战略评估报告
════════════════════════════════════════════
你的管线资产原型：[动态命名，如「脆弱的先驱者」/「拥挤赛道的优化者」]
[2-3 句整体概况]
象限拆解：
📊 生物学与靶点：[Level 1/2/3] - [优势与致命弱点]
📊 药物形式与化学：[Level 1/2/3] - [优势与致命弱点]
📊 临床与监管：[Level 1/2/3] - [优势与致命弱点]
📊 商业与知识产权：[Level 1/2/3] - [优势与致命弱点]
跨象限动态分析：
• 核心瓶颈：[如：极佳生物学机制被糟糕成药性阻碍]
• 虚假创新警告：[指出自欺欺人环节]
• SoC 演变风险：[可能淘汰该项目的竞争对手/新技术]
你必须解决的核心战略问题：
[下一轮融资或 IND 前必须解决的唯一致命缺陷]
未来 90 天去风险战略：
• 一击必杀实验（Killer Experiment）：[证伪核心假设的具体实验]
• 竞争情报任务：[必须收集的竞争对手数据]
• 监管动作：[应对准备]
战略外挂评估：
[评估 AI、加速批准等捷径的使用及科学根基是否支撑]
残酷的真相（THE HARD TRUTH）：
[1-2 段直言不讳的坦诚反馈，告知项目可能死亡的原因及存活条件]
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 · 123 lines · 189 tokens per session scan A dab2f364985f
pharma-asset-strategist is a skill published in the GitHub repository du-par/pharma-invest-skills (10 stars, last pushed 4mo ago), licensed MIT. It adds 189 tokens to every session and 1,798 once invoked, about $0.0009 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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