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Skills clinicaltrials-gov-parser

'Monitor and summarize competitor clinical trial status changes from

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 "$T/skills/aipoch-ai/clinicaltrials-gov-parser" ~/.claude/skills/openclaw-skills-clinicaltrials-gov-parser && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/aipoch-ai/clinicaltrials-gov-parser" ~/.openclaw/skills/openclaw-skills-clinicaltrials-gov-parser && rm -rf "$T"
manifest: skills/aipoch-ai/clinicaltrials-gov-parser/SKILL.md
tags
#pharma#clinical-trials#monitoring#api#data-extraction
source content

ClinicalTrials.gov Parser

Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.

Use Cases

  • Trial Monitoring: Track status changes of specific clinical trials
  • Competitive Intelligence: Monitor competitor trial activities and milestones
  • Recruitment Tracking: Get updates on enrollment status
  • Completion Alerts: Monitor trial completion and results posting

Parameters

ParameterTypeDefaultRequiredDescription
--sponsor
string-NoTrial sponsor name
--condition
string-NoMedical condition/disease
--status
string-NoTrial status (Recruiting, Completed, etc.)
--trials
string-NoComma-separated trial IDs (NCT numbers)
--output
stringjsonNoOutput format (json, csv)
--days
int30NoNumber of days for monitoring

Usage

from scripts.main import ClinicalTrialsMonitor

# Initialize monitor
monitor = ClinicalTrialsMonitor()

# Search for trials
trials = monitor.search_trials(
    sponsor="Pfizer",
    condition="Diabetes",
    status="Recruiting"
)

# Get trial details
trial = monitor.get_trial("NCT05108922")

# Check for status changes
changes = monitor.check_status_changes(trial_ids=["NCT05108922"])

CLI Usage

# Search trials
python scripts/main.py search --sponsor "Pfizer" --condition "Diabetes"

# Get trial details
python scripts/main.py get NCT05108922

# Monitor status changes
python scripts/main.py monitor --trials NCT05108922,NCT05108923 --output json

# Generate summary report
python scripts/main.py report --sponsor "Pfizer" --days 30

API Methods

MethodDescription
search_trials()
Search trials with filters
get_trial(nct_id)
Get detailed trial information
check_status_changes()
Check for status updates
get_recruitment_status()
Get enrollment updates
generate_summary()
Generate competitor summary

Technical Details

  • API: ClinicalTrials.gov API v2
  • Rate Limit: 10 requests/second
  • Data Format: JSON
  • Difficulty: Medium

References

  • See 
    references/api-docs.md
    for API documentation
  • See 
    references/status-codes.md
    for trial status definitions
  • See 
    references/examples.md
    for usage examples

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

# Python dependencies
pip install -r requirements.txt

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