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competitor-trial-monitor（竞争对手试用监视器）

Agent Skill

competitor-trial-monitor 用于补充开发相关能力，适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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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7,099

周安装

290

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下载量

2,274

OpenClaw

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

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：competitor-trial-monitor（竞争对手试用监视器）
来源仓库：https://github.com/aipoch-ai/competitor-trial-monitor
安装命令：
openclaw skills install competitor-trial-monitor
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 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。

ClawHubOpenClaw

openclaw skills install competitor-trial-monitor

简介

competitor-trial-monitor 监控竞争对手临床试验进展并生成市场风险预警。

适用于制药、医疗器械或生物科技企业的研发管线与商业化风险评估场景。
输出包含试验阶段、入组人数与关键节点的时间轴与影响分析。
安装命令为 openclaw skills install competitor-trial-monitor，需配置医药数据库访问权限。
数据来源于公开注册平台，建议结合内部医学专家解读，避免仅凭进度推断疗效。

SKILL.md

name: competitor-trial-monitor
description: Monitor competitor clinical trial progress and alert on market risks
version: 1.0.0
category: Pharma
tags: []
author: AIPOCH
license: MIT
status: Draft
risk_level: High
skill_type: Hybrid (Tool/Script + Network/API)
owner: AIPOCH
reviewer
last_updated: 2026-02-06

Competitor Trial Monitor (ID: 178)

Monitor competitor clinical trial progress and alert on market risks.

Features

Monitor changes in clinical trial status for specified competitors
Track key milestones: enrollment completion, data unblinding, final results publication
Alert on potential market competition risks

Data Sources

ClinicalTrials.gov - US Clinical Trials Registry
EU Clinical Trials Register - EU Clinical Trials Registry
WHO ICTRP - International Clinical Trials Registry Platform

Parameters

Commands

Command	Description	Parameters
`add`	Add trial to watchlist	`--nct` (required), `--company`, `--drug`, `--indication`
`list`	List all monitored trials	None
`remove`	Remove trial from watchlist	`--nct` (required)
`scan`	Scan for updates	None
`report`	Generate risk report	`--days` (default: 30)

Command Parameters

add command:

Parameter	Type	Default	Required	Description
`--nct`	string	-	Yes	ClinicalTrials.gov NCT ID
`--company`	string	Unknown	No	Competitor company name
`--drug`	string	Unknown	No	Drug name
`--indication`	string	Unknown	No	Indication/disease

remove command:

Parameter	Type	Default	Required	Description
`--nct`	string	-	Yes	NCT ID to remove

report command:

Parameter	Type	Default	Required	Description
`--days`	int	30	No	Report time range in days

Usage

Add Monitoring Target

python scripts/main.py add --nct NCT05108922 --company "Pfizer" --drug "PF-07321332" --indication "COVID-19"

Scan for Updates

python scripts/main.py scan

View Monitoring List

python scripts/main.py list

Remove Monitoring Target

python scripts/main.py remove --nct NCT05108922

Generate Risk Report

python scripts/main.py report --days 30

Data Storage

Monitoring configuration and data stored in ~/.openclaw/competitor-trial-monitor/:

watchlist.json - Monitoring list
history/ - Historical snapshots
alerts/ - Alert records

Alert Rules

Event	Risk Level	Description
Enrollment Completion	🟡 Medium	Competitor enters next phase
Data Unblinding	🔴 High	Results about to be announced
Results Publication	🔴 High	Direct impact on market competition
Regulatory Submission	🔴 High	Marketing application in progress
Approval Granted	🔴 Critical	Direct competition begins

Dependencies

pip install requests python-dateutil

Configuration File

~/.openclaw/competitor-trial-monitor/config.json:

{
  "alert_channels": ["feishu"],
  "scan_interval_hours": 24,
  "risk_threshold": "medium"
}

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python scripts with tools	High
Network Access	External API calls	High
File System Access	Read/write data	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Data handled securely	Medium

Security Checklist

[ ] No hardcoded credentials or API keys
[ ] No unauthorized file system access (../)
[ ] Output does not expose sensitive information
[ ] Prompt injection protections in place
[ ] API requests use HTTPS only
[ ] Input validated against allowed patterns
[ ] API timeout and retry mechanisms implemented
[ ] Output directory restricted to workspace
[ ] Script execution in sandboxed environment
[ ] Error messages sanitized (no internal paths exposed)
[ ] Dependencies audited
[ ] No exposure of internal service architecture

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

[ ] Successfully executes main functionality
[ ] Output meets quality standards
[ ] Handles edge cases gracefully
[ ] Performance is acceptable

Test Cases

Basic Functionality: Standard input → Expected output
Edge Case: Invalid input → Graceful error handling
Performance: Large dataset → Acceptable processing time

Lifecycle Status

Current Stage: Draft
Next Review Date: 2026-03-06
Known Issues: None
Planned Improvements:

- Performance optimization - Additional feature support

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能力概览

能力 1

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用；具体调用方式请以来源页面和 README 为准。

平台分布

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权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API，使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在 warning/failed 结果，不能写成本站确认安全。当前只有一个来源，正式发布前建议补源仓库或其他目录站核验。

来源信息

GitHub 仓库

github.com

/aipoch-ai/competitor-trial-monitor

SKILL.md 来源

clawhub.ai

/aipoch-ai/competitor-trial-monitor

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