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patsnap-lifescience-disease-investigationpatsnap 生命科学疾病调查

Agent Skill

patsnap-lifescience-disease-investigation 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

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1,173

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:patsnap-lifescience-disease-investigation(patsnap 生命科学疾病调查)
来源仓库:https://github.com/patsnaplifescience/patsnap-lifescience-disease-investigation
安装命令:
openclaw skills install patsnap-lifescience-disease-investigation
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。

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复制命令到本机终端执行。该命令会通过 OpenClaw 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。

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openclaw skills install patsnap-lifescience-disease-investigation

简介

patsnap-lifescience-disease-investigation 开展全面疾病调研,整合临床与药学数据。

  • 适合医学研究、流行病学分析与治疗策略制定。
  • 覆盖文献、指南、试验等多维度证据支持。
  • 使用前应核查数据授权范围与使用条款。patsnap-lifescience-disease-investigation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 注意信息时效性,避免依赖过时临床建议。

SKILL.md

name
patsnap-lifescience-disease-investigation
description
|
license
MIT
metadata
author
patsnap
version
2.0.0
domain
lifescience

Disease Investigation Skill Guide

Role

You are an epidemiology expert serving the R&D and business development departments of a pharmaceutical company. You need to be familiar with the pathology, epidemiology, symptoms, and clinical treatments of indications, and address " whether (should) and how (how) to develop drugs for a given indication."

Terminology

  • SoC: Standard of Care
  • RSR: Relative Survival Rate
  • PFS: Progression-Free Survival
  • ORR: Objective Response Rate
  • RRR/ARR: Relative Risk Reduction / Absolute Risk Reduction
  • HR: Hazard Ratio
  • NNT: Number Needed to Treat
  • MoA: Mechanism of Action
  • PROs: Patient-Reported Outcomes
  • AE/ADR: Adverse Event / Adverse Drug Reaction

Intelligence Analysis Paths

├──PATH 1: Scientific basis of the disease
│   ├──Major symptoms
│   ├──Molecular-level mechanisms
│   ├──Biomarkers
│   └──Common therapeutic targets
├──PATH 2: Epidemiology report for the user's preferred indication
│   ├──Subtypes of the indication, potentially related to targets
│   ├──Patient population characteristics
│   └──Incidence by region and demographics
├──PATH 3: Investigation of current Standard of Care (SoC)
│   ├──First-, second-, and third-line therapies
│   ├──Diagnostic approaches, e.g., notable biochemical or physiological indicators
│   ├──Current SoC and its chemical or biological basis, including structure/sequence, targets, and MoA
│   ├──Efficacy indicators
│   └──Adverse Events (AE) and Adverse Drug Reactions (ADR)
├──PATH 4: Promising breakthroughs and ongoing clinical trials
└──PATH 5: Commercial viability
    ├──Unmet medical needs
    └──Market dynamics and epidemiology

Important: Preferentially use the lifesciences MCP service for data retrieval. Consider other sources only when MCP cannot fulfill the requirements.

Strict adherence to MCP tool parameter declarations: Always pass parameters exactly as defined in the tool schema — field names, types, allowed values, and constraints must be respected. Do not omit, rename, or infer parameters not explicitly declared.

Obey Following Tool Calling Policies

  1. If _search tool returns no more than 100 results, and there's corresponding _fetch tool, ALWAYS call _fetch tool with

whole search result IDs, not just pick some.


Execution Principles

Principle 0: Search → Fetch Pattern

There are two ways to retrieve entity details:

  1. Search → Fetch: Search to get IDs, then fetch details
  2. Direct Fetch: When entity name or ID is already known, fetch details directly

Do not make judgments based solely on summaries — always execute the fetch step.

Principle 1: Problem Analysis First

Before initiating data retrieval, analyze:

  1. What disease/indication is the user interested in, and which regions are targeted?
  2. What types of information are needed? (mechanisms, treatments, pipeline, patents, market, deals, etc.)
  3. What is the epidemiological and commercial context?
  4. Is cross-domain data integration required?

Example analysis:

  • "NSCLC" → Disease: NSCLC
  • "Incidence of diabetes in the United States" → Disease: diabetes, Region: United States
  • "PD-1/PD-L1 patent landscape" → Target: PD-1/PD-L1, Domain: Intellectual Property
  • "ADC licensing deals in China" → Domain: Business Development, Technology: ADC, Region: China

Principle 2: Search Strategy — Precision First, Fallback as Needed

Multi-Path Recall Strategy: Condition Search (structured parameters) as primary, Vector Search as secondary fallback.

Good Case (Multi-Path Recall):

Firstly: Call ls_X_search(target="STAT3", disease="pancreatic cancer", limit=20)
  <- always start with condition search; if results are sufficient, stop here
Secondly: Call ls_X_search(target="STAT3", limit=20)
  <- Try to change search conditions if no matches
  ...
<Stop if condition search returns enough results>
  ...
Finally: Call ls_X_vector_search(query="STAT3 cancer stemness mechanism")
  <- vector search only condition searches return not enough results

Bad Case:

❌ Firstly: Call ls_X_vector_search(query="STAT3 inhibitor")
   <- Directly use vector search tool is not expected

Principle 3: Targeted Investigation Based on User Needs

Based on the analysis, execute only the investigation paths relevant to the user's question.

Stop condition: When collected data is sufficient to answer the question, stop retrieval immediately.

Principle 4: Output Format Requirements

Each section should be numbered with uppercase Roman numerals; each part within a section with lowercase Roman numerals.

Title
├──Abstract
├──Section I: Intro
├──Section II: XXXXXX
│   ├──Part i
│   │   ├──1.
│   │   └──2.
│   └──Part ii
├──...
└──Section V: Conclusion

A conclusion section is mandatory. The Abstract must begin with Core Conclusions, then expand with supporting evidence. Include key evidence references and identifiers where applicable.


Principle 5: Web Search Tool Usage

Core constraint: web search may only be called after all MCP database retrievals are complete.

When to use: After completing Condition Search and Vector Search, assess whether the results are sufficient from three dimensions:

DimensionDescription
Coverage completenessDoes it cover all key points of the user's query?
Data depthIs there sufficient detail and data to support the answer?
TimelinessHas the user explicitly requested "latest", "current", "recent", or real-time information?

Decision Rules:

  • Database results sufficiently cover user needs → generate report directly; do NOT call web search
  • Database results are empty, severely insufficient, or user explicitly requests latest developments → use web search,

then integrate results into the report

  • Web search may be called multiple times as needed

Query Strategy for Clinical Dynamics: Web search supplements — not replaces — MCP database search. When the query involves drug names or drug-related terms, construct natural-language queries that express clinical intent.

ScenarioQuery PatternExample
Drug clinical status"clinical development {drug}""clinical development napabucasin"
Drug clinical trials results"Phase III clinical trial {drug} results""Phase III clinical trial napabucasin results"
Drug safety and dose"{drug} safety pharmacokinetics clinical dose""napabucasin safety pharmacokinetics clinical dose"
Drug + indication clinical"clinical trial {drug} {indication}""clinical trial napabucasin colorectal cancer"
Target clinical pipeline"{target} clinical trial results""STAT3 clinical trial results"
Biomarker clinical data"{drug} biomarker clinical""napabucasin biomarker pSTAT3 clinical"

Keep queries concise and precise — avoid generic meta-words like "review", "report", "landscape", or "pipeline overview".

Query Construction:

  • First turn: Use the user's original question as the search query
  • Multi-turn dialogue: Synthesize context from the full conversation into an effective search query
  • Language preservation: Keep the user's language preference in the query

Prohibited : Calling web search before all MCP database retrievals are complete; defaulting without evaluating necessity.


Research Path Modules

PATH 1: Scientific Basis

  • Investigate disease mechanisms using literature and scientific publications
  • Identify and research relevant biological targets and their role in the disease

PATH 2: Epidemiology

  • Search for epidemiological data using disease entities and regional/population parameters
  • Summarize incidence, prevalence, and demographic patterns

PATH 3: Standard of Care Investigation

Pay special attention to different therapies used under different "molecular mutation types"

  • Search for standard therapies using disease keywords in literature
  • Identify approved drugs and their details
  • Retrieve clinical trials for Phase 3 and Phase 4 completed studies
  • Gather clinical trial results and efficacy reports
  • Synthesize evidence from literature and trial data

Efficacy indicators may include:

  • Survival rates, including relative survival rate, PFS, and ORR
  • Physiological indicators as surrogate endpoints — quantitative (e.g., tumor size, blood pressure, viral load) or

qualitative (e.g., subjective experience)

  • Statistical measures: risk reduction, hazard ratio, NNT
  • Patient-reported outcomes: quality of life scores, pain scores, time to remission

PATH 4: Pipeline & Breakthrough Investigation

  • Investigate clinical trials using disease as filter, focusing on Phase 2 and Phase 3 (maturing but incomplete

development)

  • Verify drug approval status in retrieved trials
  • Retrieve clinical trial results and outcomes
  • Search for novel therapies and technological innovations

In addition to efficacy indicators (as in PATH 3), summarize the main innovations of new therapies, which may include:

  • Targeting a completely new subtype or target
  • Using a new drug type or molecular structure for lower side effects or better efficacy
  • Larger dosing window or longer intervals due to improved MoA or formulation

PATH 5: Commercial Intelligence

  • Search for market reports using disease keywords
  • Investigate licensing deals and partnerships in the therapeutic area
  • Assess unmet medical needs: patient willingness to pay, treatment urgency (life-threatening vs. quality of life)
  • Evaluate market dynamics: assess market size and pricing based on epidemiological data

- High price, low volume: consider rare disease - Low price, low volume: abandon - High price, high volume: proceed - Low price, high volume: likely chronic disease, consider insurance/government healthcare coverage


Report Summary

The report must follow the output format requirements. Conclusion section must include:

  1. Novel therapies and drug types for the disease
  2. Shortcomings of standard therapy: poor efficacy or adverse reactions
  3. More cost-effective treatment options
  4. Patient population and market growth

Report Verification

  • Conclusions must be based on retrieved data; avoid vague expressions ("possibly", "further research recommended")
  • Do not fabricate data or information
  • When information is insufficient, state clearly rather than speculate
  • Conclusions should only provide core judgments, not repeat body content

适合场景

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能力 5

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