Generate ethical, compliant, and patient-friendly recruitment advertisements for clinical trials.
Generate ethical, compliant, and patient-friendly recruitment advertisements for clinical trials.
scripts/main.py.references/ for task-specific guidance.See ## Prerequisites above for related details.
Python: 3.10+. Repository baseline for current packaged skills.Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.See ## Usage above for related details.
cd "20260318/scientific-skills/Academic Writing/patient-recruitment-ad-gen"
python -m py_compile scripts/main.py
python scripts/main.py --help
Example run plan:
CONFIG block or documented parameters if the script uses fixed settings.python scripts/main.py with the validated inputs.See ## Workflow above for related details.
scripts/main.py.references/ contains supporting rules, prompts, or checklists.Use this command to verify that the packaged script entry point can be parsed before deeper execution.
python -m py_compile scripts/main.py
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
This skill helps researchers, CROs, and medical institutions create patient recruitment advertisements that meet Institutional Review Board (IRB) / Ethics Committee (EC) requirements while being accessible and encouraging to potential participants.
Trial Identity
Purpose Statement
Eligibility Criteria
Study Procedures
Risks and Benefits
Confidentiality
Voluntary Participation
Contact Information
{
"disease_condition": str, # Target disease/condition
"study_phase": str, # Phase I/II/III/IV
"intervention_type": str, # Drug, device, procedure, etc.
"target_population": str, # Demographics, age range
"study_duration": str, # Expected time commitment
"site_location": str, # Study site location
"compensation": Optional[str], # Participant payment (if any)
"pi_name": str, # Principal Investigator
"contact_info": str, # Phone/email for inquiries
"irb_reference": str # IRB/EC approval number
}
python /Users/z04030865/.openclaw/workspace/skills/patient-recruitment-ad-gen/scripts/main.py \
--disease "Type 2 Diabetes" \
--phase "Phase II" \
--intervention "Investigational oral medication" \
--population "Adults 18-65 with T2DM" \
--duration "12 weeks, 6 clinic visits" \
--location "City Medical Center, Building C" \
--pi "Dr. Sarah Chen" \
--contact "(555) 123-4567 or [email protected]" \
--irb "IRB-2024-001"
Generates a structured recruitment ad with:
See references/ folder for:
fda_guidance.md - FDA guidance on informed consentema_guidelines.md - European ethics requirementsich_gcp.md - ICH-GCP E6(R2) recruitment provisionsplain_language_guide.pdf - NIH Plain Language guidelinestemplate_examples/ - Sample ads for different therapeutic areasTechnical Difficulty: Medium
Category: Pharma / Clinical Research
Last Updated: 2026-02-05
| Risk Indicator | Assessment | Level |
|---|---|---|
| Code Execution | Python/R scripts executed locally | Medium |
| Network Access | No external API calls | Low |
| File System Access | Read input files, write output files | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Output files saved to workspace | Low |
No additional Python packages required.
Every final response should make these items explicit when they are relevant:
scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.This skill accepts requests that match the documented purpose of patient-recruitment-ad-gen 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:
patient-recruitment-ad-genonly handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.
Use the following fixed structure for non-trivial requests:
If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.