fda-guideline-search

name	fda-guideline-search
description	Search FDA industry guidelines by therapeutic area or topic.
license	MIT
author	AIPOCH

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

FDA Guideline Search

Quickly search and retrieve FDA industry guidelines by therapeutic area.

When to Use

• Use this skill when the task needs Search FDA industry guidelines by therapeutic area or topic.
• 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.

Key Features

See ## Features above for related details.

• Scope-focused workflow aligned to: Search FDA industry guidelines by therapeutic area or topic.
• Packaged executable path(s): scripts/main.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

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.

Example Usage

See ## Usage above for related details.

cd "20260318/scientific-skills/Evidence Insight/fda-guideline-search"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/main.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/main.py.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

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

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.

Features

• Search FDA guidelines by therapeutic area (oncology, cardiology, neurology, etc.)
• Filter by document type (draft, final, ICH guidelines)
• Download and cache guideline documents
• Search within document content

Usage

Python Script

python scripts/main.py --area <therapeutic_area> [options]

Parameters

Parameter	Type	Default	Required	Description
--area	string	-	Yes	Therapeutic area (oncology, cardiology, rare-disease)
--type	string	all	No	Document type (all, draft, final, ich)
--year	string	-	No	Filter by year (e.g., 2023, 2020-2024)
--download	flag	false	No	Download PDF to local cache
--search	string	-	No	Search term within documents
--limit	int	20	No	Max results (1-100)

Examples

# Search oncology guidelines
python scripts/main.py --area oncology

# Search for rare disease draft guidelines
python scripts/main.py --area "rare disease" --type draft

# Search with download
python scripts/main.py --area cardiology --download --limit 10

Technical Details

• Source: FDA CDER/CBER Guidance Documents Database
• API: FDA Open Data / Web scraping with rate limiting
• Cache: Local PDF storage in references/cache/
• Difficulty: Medium

Output Format

Results are returned as structured JSON:

{
  "query": {
    "area": "oncology",
    "type": "all",
    "limit": 20
  },
  "total_found": 45,
  "guidelines": [
    {
      "title": "Clinical Trial Endpoints for the Approval of Cancer Drugs...",
      "document_number": "FDA-2020-D-0623",
      "issue_date": "2023-03-15",
      "type": "Final",
      "therapeutic_area": "Oncology",
      "pdf_url": "https://www.fda.gov/.../guidance.pdf",
      "local_path": "references/cache/..."
    }
  ]
}

References

• FDA Search Strategy
• Therapeutic Area Mappings
• FDA API Documentation

Limitations

• Rate limited to 10 requests/minute to respect FDA servers
• Some historical documents may not have digital PDFs
• ICH guidelines require separate search scope

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

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 fda-guideline-search 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:

fda-guideline-search 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.