clinicaltrials-gov-parser

name	clinicaltrials-gov-parser
description	Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.
license	MIT
author	AIPOCH

Source: https://github.com/aipoch/medical-research-skills

ClinicalTrials.gov Parser

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

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py --help

When to Use

• Use this skill when the task needs Monitor and summarize competitor clinical trial status changes from ClinicalTrials.gov.
• Use this skill for evidence insight tasks that require explicit assumptions, bounded scope, and a reproducible output format.
• Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

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

Parameter	Type	Default	Required	Description
--sponsor	string	-	No	Trial sponsor name
--condition	string	-	No	Medical condition/disease
--status	string	-	No	Trial status (Recruiting, Completed, etc.)
--trials	string	-	No	Comma-separated trial IDs (NCT numbers)
--output	string	json	No	Output format (json, csv)
--days	int	30	No	Number 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

Method	Description
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 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

# 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

Output Requirements

Every final response should make these items explicit when they are relevant:

• Objective or requested deliverable
• Inputs used and assumptions introduced
• Workflow or decision path
• Core result, recommendation, or artifact
• Constraints, risks, caveats, or validation needs
• Unresolved items and next-step checks

Error Handling

• If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
• If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
• If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
• Do not fabricate files, citations, data, search results, or execution outcomes.

Input Validation

This skill accepts requests that match the documented purpose of clinicaltrials-gov-parser and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

clinicaltrials-gov-parser only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

When Not to Use

• Do not proceed when required input files, identifiers, parameters, or context are missing — ask the user to provide them first.
• Do not assume capabilities beyond this skill's declared scope when the user requests external operations or inferences.
• Do not proceed without user confirmation when overwriting existing results, executing high-cost batch operations, or expanding task scope.

Required Inputs

Field	Required	Format/Source	Example	If Missing
User task description	Yes	Text	Research question, writing goal, analysis objective	Stop and ask user to provide
Primary input material	Depends on task	Text, file path, ID, table, or literature	PMID, PDF, CSV, DOCX, keywords, etc.	Specify which material type is missing
Output preference	No	Text	Language, format, target journal, template	Use skill default format

Output Contract

• Primary output: Structured result or target file aligned with this skill's objective.
• Optional output: Intermediate check notes, issue list, supplementary suggestions, or generated file paths.
• Format requirement: Unless the user specifies otherwise, prefer stable, reviewable Markdown or JSON; if the skill's bundled script requires a fixed format, use that format.
• If partially complete: Must explicitly mark as PARTIAL and state which steps are completed and which remain.

Failure Handling

• Missing critical input: Explicitly state which fields, files, or identifiers are missing and pause.
• Script, template, or resource execution failure: Report the failing step, likely cause, and recovery suggestions — do not silently degrade.
• Partial completion only: Return the verified portion first, then list remaining blockers and suggested next steps.

User Checkpoints

• Before executing batch processing, overwriting files, long-running searches, or multi-stage generation, confirm scope and output format with the user.
• Before proceeding when a key judgment is ambiguous, evidence is insufficient, or the workflow is entering the next stage, confirm with the user.

Quick Validation

• Check that key scripts, templates, or reference file paths this skill depends on exist.
• Check that the final output contains the core fields, sections, or files specified for this task.
• Check that results clearly mark assumptions, limitations, and incomplete items.