Skills competitor-trial-monitor

Monitor competitor clinical trial progress and alert on market risks

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/aipoch-ai/competitor-trial-monitor" ~/.claude/skills/clawdbot-skills-competitor-trial-monitor && rm -rf "$T"
manifest: skills/aipoch-ai/competitor-trial-monitor/SKILL.md
source content

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

CommandDescriptionParameters
add
Add trial to watchlist
--nct
(required),
--company
,
--drug
,
--indication
list
List all monitored trialsNone
remove
Remove trial from watchlist
--nct
(required)
scan
Scan for updatesNone
report
Generate risk report
--days
(default: 30)

Command Parameters

add command:

ParameterTypeDefaultRequiredDescription
--nct
string-YesClinicalTrials.gov NCT ID
--company
stringUnknownNoCompetitor company name
--drug
stringUnknownNoDrug name
--indication
stringUnknownNoIndication/disease

remove command:

ParameterTypeDefaultRequiredDescription
--nct
string-YesNCT ID to remove

report command:

ParameterTypeDefaultRequiredDescription
--days
int30NoReport 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

EventRisk LevelDescription
Enrollment Completion🟡 MediumCompetitor enters next phase
Data Unblinding🔴 HighResults about to be announced
Results Publication🔴 HighDirect impact on market competition
Regulatory Submission🔴 HighMarketing application in progress
Approval Granted🔴 CriticalDirect 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 IndicatorAssessmentLevel
Code ExecutionPython scripts with toolsHigh
Network AccessExternal API callsHigh
File System AccessRead/write dataMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureData handled securelyMedium

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

  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. 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