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Competitor Trial Monitor

Name: Competitor Trial Monitor
Author: aipoch-ai

作者 AIpoch · GitHub ↗ · v0.1.0 · MIT-0

cross-platform ⚠ suspicious

233

总下载

当前安装

版本数

在 OpenClaw 中安装

/install competitor-trial-monitor

功能描述

Monitor competitor clinical trial progress and alert on market risks

使用说明 (SKILL.md)

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

安全使用建议

This skill appears to be a mostly-local monitor that fetches data from ClinicalTrials.gov and stores alerts in ~/.openclaw/competitor-trial-monitor. The main concern is inconsistency between the documentation and the code: SKILL.md advertises EU/WHO registries, Feishu alerts, and requires requests/python-dateutil, but the script only uses urllib and only queries ClinicalTrials.gov and prints/saves alerts locally. Before installing or running: 1) Review the full script to ensure there are no hidden network endpoints (the provided portion looks clean but confirm the truncated part). 2) If you expect multi-registry monitoring or push notifications (Feishu), verify those implementations or add them intentionally; do not assume they exist. 3) Consider running the script in a sandboxed account or container (so it only writes to the dedicated data directory) and monitor outbound network traffic. 4) If you will share sensitive competitor identifiers, be aware the data is stored under your home directory—move the storage to a controlled workspace or encrypt it if needed. If these mismatches worry you or you need the additional features, ask the author for an updated release or seek a variant whose code and docs align.

功能分析

Type: OpenClaw Skill Name: competitor-trial-monitor Version: 0.1.0 The competitor-trial-monitor skill is a legitimate tool designed to track clinical trial progress via the official ClinicalTrials.gov API. The Python script (scripts/main.py) implements standard monitoring logic, storing data locally in a dedicated directory (~/.openclaw/competitor-trial-monitor/) and using urllib for secure HTTPS requests to a hardcoded, reputable endpoint. No indicators of data exfiltration, malicious execution, or prompt injection were found.

能力评估

⚠ Purpose & Capability

SKILL.md states multiple data sources (ClinicalTrials.gov, EU register, WHO ICTRP) and alert channels (e.g., Feishu) and lists dependencies (requests, python-dateutil). The included script, however, only queries ClinicalTrials.gov via urllib and writes local JSON alert files/prints to console. Declared features and dependencies do not match the code, which suggests documentation drift or incomplete/incorrect implementation.

ℹ Instruction Scope

Runtime instructions map to the provided CLI and filesystem paths (~/.openclaw/competitor-trial-monitor). The script performs network calls to clinicaltrials.gov (expected) and reads/writes only to its own data directory. It does not read unrelated system files or request environment variables. However SKILL.md implies external alert delivery (Feishu) and other registries that the script does not implement; the agent instructions therefore overstate scope.

✓ Install Mechanism

This is an instruction-only skill with no install spec. The only executable artefact is the included Python script; nothing is downloaded or installed automatically by the skill bundle.

✓ Credentials

The skill requests no environment variables, credentials, or config paths beyond writing into a per-user directory under the user's home (~/.openclaw/...). No secrets are requested. This is proportionate to the stated purpose.

✓ Persistence & Privilege

always:false and the skill does not request system-wide changes or modify other skills. It stores state only under the user's home directory in a dedicated path.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install competitor-trial-monitor
安装完成后，直接呼叫该 Skill 的名称或使用 /competitor-trial-monitor 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v0.1.0

Initial release of competitor-trial-monitor. - Monitor competitor clinical trial progress across major international registries. - Track key milestones (enrollment completion, data unblinding, results) for added trials. - Command-line interface for managing watchlist, scanning updates, and generating risk reports. - Alert system categorizes market risks from trial events. - Secure local data storage and configurable alert settings. - High risk level; draft status with future performance optimizations planned.

元数据

Slug competitor-trial-monitor

版本 0.1.0

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 1

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