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Agent Skill · 研究检索

tooluniverse-drug-regulatory(工具宇宙药品监管)

tooluniverse-drug-regulatory 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

tooluniverse-drug-regulatory 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 41,772。

总安装 1,140周安装 48GitHub Stars 1,309下载 399核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:tooluniverse-drug-regulatory(工具宇宙药品监管)
来源仓库:https://github.com/mims-harvard/tooluniverse
仓库路径:skills/tooluniverse-drug-regulatory
安装命令:
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-drug-regulatory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-drug-regulatory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。tooluniverse-drug-regulatory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词或任务场景快速定位候选研究资料。通过调用工具执行搜索任务并返回匹配结果列表。需结合来源仓库 README 核验具体用法和参数格式。

安装前建议确认是否触发联网及文件读写权限。

来源仓库内路径:skills/tooluniverse-drug-regulatory

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

tooluniverse-drug-regulatory 怎么安装?

在终端执行 npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-drug-regu…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

tooluniverse-drug-regulatory 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

tooluniverse-drug-regulatory 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

tooluniverse-drug-regulatory 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tooluniverse-drug-regulatory 用的人多吗?

公开数据是累计安装 1,140 次,近一周安装 48 次,下载 399 次,GitHub 1,309 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

tooluniverse-drug-regulatory 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 1,309 星,维护活跃度相对可查。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
tooluniverse-drug-regulatory

工具宇宙药品监管 · 本页

1,1401,309只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Drug Regulatory Research

Regulatory status depends on jurisdiction. FDA approval does not equal EMA approval — check the specific market the user is asking about. Generic availability depends on BOTH patent expiry AND regulatory approval — a patent may have expired but no ANDA may yet be filed or approved. Exclusivity codes (NCE, ODE, PED) can block generics even after patent expiry; always check FDA_OrangeBook_get_exclusivity before concluding a generic can enter. A 505(b)(2) NDA is not a generic — it requires its own clinical data and gets its own exclusivity period.

LOOK UP DON'T GUESS: never assume NDA numbers, exclusivity dates, or ATC codes — always call FDAGSRS, Orange Book, and RxClass tools to retrieve current data; regulatory status changes with new approvals and expirations.

Regulatory intelligence for drugs: identify FDA substances, classify drugs by therapeutic category, check approval and generic status, retrieve label sections, and find clinical trials.

When to Use

  • "What is the FDA regulatory status of semaglutide?"
  • "Is there a generic for Humira?"
  • "What ATC class does metformin belong to?"
  • "Get adverse reactions from the ibuprofen drug label"
  • "When does the patent for Eliquis expire?"
  • "List all drugs in the ACE inhibitor class"
  • "Find clinical trials for a biosimilar of adalimumab"

NOT for (use other skills instead)

  • Drug-drug interactions -> Use tooluniverse-drug-drug-interaction
  • Pharmacogenomics / dosing by genotype -> Use tooluniverse-pharmacogenomics
  • Drug mechanism of action / target binding -> Use tooluniverse-drug-mechanism-research
  • Drug repurposing / new indications -> Use tooluniverse-drug-repurposing

Workflow Overview

Input (drug name / brand name / UNII)
  |
  v
Phase 1: Substance Identification  -- FDAGSRS_search_substances, FDAGSRS_get_substance
  |
  v
Phase 2: Drug Classification       -- RxClass_get_drug_classes, RxClass_find_classes
  |
  v
Phase 3: Approval & Generic Status -- FDA_OrangeBook_search_drug, FDA_OrangeBook_check_generic_availability
  |
  v
Phase 4: Patent & Exclusivity      -- FDA_OrangeBook_get_patent_info, FDA_OrangeBook_get_exclusivity
  |
  v
Phase 5: Label Parsing             -- DailyMed_parse_adverse_reactions, DailyMed_parse_dosing, etc.
  |
  v
Phase 6: Clinical Trials           -- search_clinical_trials
  |
  v
Phase 7: Pharmacovigilance         -- FAERS_count_reactions_by_drug_event (param: medicinalproduct)
  |
  v
Phase 8: Literature & Approval     -- PubMed_search_articles, OpenFDA_get_approval_history, RxNorm_get_drug_names
Supplementary tools (not in core phases but useful): - OpenFDA_get_approval_history — full FDA submission/approval history (requires operation param) - FAERS_count_reactions_by_drug_event — top adverse events by report count (param: medicinalproduct, ALL CAPS) - RxNorm_get_drug_names — resolve drug to RXCUI and brand names - drugbank_vocab_search — DrugBank ID, CAS, UNII lookup - PubMed_search_articles — regulatory and clinical literature

Phase 1: Substance Identification (FDAGSRS)

FDAGSRS_search_substances: query (string REQUIRED -- drug name, UNII, InChIKey, or formula), substance_class (string, optional: "chemical"/"protein"/"nucleic acid"/"polymer"/"mixture"), limit (int, 1-50, default 10). Returns {status, data: {substances: [{unii, name, substance_class, status, cross_references: [{type, value}]}]}}.

  • cross_references contains DrugBank IDs, WHO-ATC codes, CAS numbers, CFR citations.
  • Use to get the official UNII identifier before calling FDAGSRS_get_substance.

FDAGSRS_get_substance: unii (string REQUIRED, 10-char FDA UNII code). Returns complete substance record including all synonyms, names, structure, and cross-references.

  • Provides definitive list of all registered names (INN, USAN, brand, chemical).

FDAGSRS_get_structure: unii (string REQUIRED). Returns {status, data: {smiles, formula, inchikey, molfile, molecular_weight, stereochemistry, optical_activity}}.

  • Only works for chemical substances; returns error for biologics, mixtures, polymers.
# Full substance lookup workflow
search = tu.tools.FDAGSRS_search_substances(query="semaglutide")
unii = search["data"]["substances"][0]["unii"]
full = tu.tools.FDAGSRS_get_substance(unii=unii)

Phase 2: Drug Classification (RxClass)

RxClass_get_drug_classes: drug_name (string, drug name), rxcui (string, RxNorm RXCUI -- alternative to drug_name), rela_source (string, optional: "ATC"/"FDASPL"/"MESH"/"VA"), limit (int, default 20). Returns {status, data: {classes: [{class_id, class_name, class_type, rela}]}}.

  • Returns ALL classification systems unless rela_source filters to one.
  • class_type values: "ATC1-4", "EPC" (FDA Established Pharmacologic Class), "MoA", "VA", "MESH".
  • Use to find a drug's ATC code, pharmacological class, mechanism of action label.

RxClass_find_classes: query (string REQUIRED, keyword e.g., "beta blocker"), class_type (string, optional: "ATC1-4"/"EPC"/"MoA"), limit (int, default 20). Returns matching drug classes with class IDs.

  • Use when you need to find a class ID before calling RxClass_get_class_members.

RxClass_get_class_members: class_id (string REQUIRED, e.g., "M01AE"), rela_source (string, optional: "ATC"/"FDASPL"), ttys (string, optional: "IN" for ingredients), limit (int, default 50). Returns all drug ingredients in the class with RXCUIs and names.

  • ttys="IN" restricts to active ingredient-level entries (recommended).
# Find all proton pump inhibitors
classes = tu.tools.RxClass_find_classes(query="proton pump inhibitor", class_type="EPC")
class_id = classes["data"]["classes"][0]["class_id"]
members = tu.tools.RxClass_get_class_members(class_id=class_id, ttys="IN")

Phase 3: Approval & Generic Status (FDA Orange Book)

FDA_OrangeBook_search_drug: brand_name (string), generic_name (string), application_number (string), limit (int, default 10). Returns {status, data: {products: [{brand_name, generic_name, dosage_form, strength, te_code, application_number, approval_date}]}}.

  • Use brand name (UPPERCASE) or generic name to find NDA/ANDA numbers and approval info.
  • te_code: Therapeutic Equivalence code (e.g., "AB" = therapeutically equivalent).

FDA_OrangeBook_check_generic_availability: brand_name (string), generic_name (string). Returns {status, data: {reference_listed_drug, generics_available: bool, generics_count, generic_products: [...]}}.

  • Primary tool for "is there a generic?" questions.

FDA_OrangeBook_get_te_code: No special params beyond brand_name/application_number. Returns therapeutic equivalence codes for substitutability assessment.

FDA_OrangeBook_get_approval_history: application_number (string, e.g., "NDA020402"). Returns chronological approval history including supplemental approvals and label changes.

# Check generic availability
result = tu.tools.FDA_OrangeBook_check_generic_availability(brand_name="LIPITOR")
# result["data"]["generics_available"] -> True
# result["data"]["generics_count"] -> N

Phase 4: Patent & Exclusivity

FDA_OrangeBook_get_patent_info: application_number (string), brand_name (string). Returns patent information. Note: Full patent numbers and expiration dates require Orange Book data files.

FDA_OrangeBook_get_exclusivity: application_number (string), brand_name (string). Returns {status, data: {exclusivities: [{exclusivity_code, exclusivity_date, description}]}}.

  • exclusivity_code values: "NCE" (New Chemical Entity, 5 years), "ODE" (Orphan Drug, 7 years), "PED" (Pediatric, 6 months), "NP" (New Product), "M" (new formulation).

Phase 5: Label Parsing (DailyMed)

All DailyMed parse tools accept either setid (SPL Set ID UUID) OR drug_name (auto-lookup). Using drug_name is recommended when the setid is unknown.

DailyMed_parse_adverse_reactions: setid or drug_name. Returns structured adverse reaction table with frequencies and severity.

DailyMed_parse_dosing: setid or drug_name. Returns dosage and administration section (doses, schedules, renal/hepatic adjustments).

DailyMed_parse_contraindications: setid or drug_name. Returns contraindications section.

DailyMed_parse_drug_interactions: setid or drug_name. Returns drug-drug interaction section with clinical management guidance.

DailyMed_parse_clinical_pharmacology: setid or drug_name. Returns PK/PD data (Cmax, AUC, half-life, protein binding, metabolism pathway).

DailyMed_search_spls: drug_name (string), returns SPL Set IDs for that drug. Use to find setid when needed explicitly.

# Parse adverse reactions for apixaban
ae = tu.tools.DailyMed_parse_adverse_reactions(drug_name="apixaban")

Phase 6: Clinical Trials

search_clinical_trials: condition (string), intervention (string), query_term (string), pageSize (int, alias: max_results/limit), overall_status (array, alias: status). Returns {status, data: {studies: [{NCT ID, brief_title, brief_summary, overall_status, phase}], total_count}}.

  • Use intervention for drug name, condition for disease.
  • Filter overall_status=["RECRUITING"] for active enrollment.
  • total_count may be None even when results exist; check len(studies) > 0.
# Find recruiting trials for a biosimilar
trials = tu.tools.search_clinical_trials(
    intervention="adalimumab biosimilar",
    overall_status=["RECRUITING"],
    pageSize=10
)

Example Workflows

Workflow 1: Full Regulatory Profile for a Drug

1. FDAGSRS_search_substances(query="apixaban")
   -> UNII, substance class, ATC/DrugBank cross-refs

2. RxClass_get_drug_classes(drug_name="apixaban", rela_source="ATC")
   -> ATC code B01AF02 (direct factor Xa inhibitor)

3. FDA_OrangeBook_search_drug(brand_name="ELIQUIS")
   -> NDA206518, approval date, TE code

4. FDA_OrangeBook_check_generic_availability(brand_name="ELIQUIS")
   -> Generic availability status

5. FDA_OrangeBook_get_exclusivity(brand_name="ELIQUIS")
   -> Exclusivity codes and expiration dates

6. DailyMed_parse_adverse_reactions(drug_name="apixaban")
   -> Bleeding rates and other AEs from label

Workflow 2: List All Drugs in a Therapeutic Class

1. RxClass_find_classes(query="ACE inhibitor", class_type="EPC")
   -> class_id for "Angiotensin-Converting Enzyme Inhibitor"

2. RxClass_get_class_members(class_id=<id>, ttys="IN")
   -> All ACE inhibitors (enalapril, lisinopril, ramipril, etc.)

3. For each drug: RxClass_get_drug_classes(drug_name=drug)
   -> Confirm ATC code and additional classifications

Workflow 3: Drug Label Review

1. DailyMed_parse_adverse_reactions(drug_name="metformin")
   -> AE frequencies (GI: lactic acidosis, nausea, diarrhea)

2. DailyMed_parse_contraindications(drug_name="metformin")
   -> eGFR thresholds, renal impairment contraindications

3. DailyMed_parse_drug_interactions(drug_name="metformin")
   -> Iodinated contrast, carbonic anhydrase inhibitor interactions

4. DailyMed_parse_clinical_pharmacology(drug_name="metformin")
   -> Half-life, renal clearance, bioavailability

Common Mistakes

  • Orange Book brand_name must be UPPERCASE (e.g., "LIPITOR")
  • FDAGSRS_get_substance requires UNII, not drug name — call FDAGSRS_search_substances first
  • FDAGSRS_get_structure only works for chemical substances, not biologics
  • RxClass_get_class_members: pass ttys="IN" to restrict to active ingredients
  • search_clinical_trials overall_status must be an array: ["RECRUITING"]

Reasoning Framework

Interpretation Guidance

Approval pathways: A 505(b)(1) NDA is a full new drug application with complete safety/efficacy data from the sponsor. A 505(b)(2) NDA relies partly on published literature or FDA findings for an already-approved drug (common for reformulations, new routes). An ANDA (Abbreviated NDA) is the generic pathway requiring only bioequivalence to the reference listed drug.

Orange Book patent and exclusivity: NCE (New Chemical Entity) exclusivity gives 5 years of data protection. ODE (Orphan Drug Exclusivity) gives 7 years. PED (Pediatric) adds 6 months to existing patents/exclusivity. A TE code of "AB" means the generic is therapeutically equivalent and substitutable. No TE code or "BX" means substitutability is not established.

DailyMed label sections: The "Adverse Reactions" section distinguishes clinical trial rates (controlled) from post-marketing reports (uncontrolled, signal-only). "Contraindications" are absolute; "Warnings and Precautions" are conditional risks. "Clinical Pharmacology" provides PK parameters (Cmax, AUC, half-life) essential for drug interaction and dosing assessment.

Synthesis Questions

A complete drug regulatory report should answer:

  1. What is the current FDA approval status and pathway (NDA vs ANDA vs 505(b)(2))?
  2. Are generic equivalents available, and what is their therapeutic equivalence rating?
  3. When do key patents and exclusivities expire (or have they already)?
  4. What drug class does this belong to (ATC, EPC, MoA), and what are peer drugs in the class?
  5. What are the most clinically significant adverse reactions and contraindications from the label?

平台分布

Codex

38.27%
按下载量换算153

Claude

26.69%
按下载量换算106

Cursor

19.86%
按下载量换算79

Gemini CLI

9.69%
按下载量换算39

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权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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