SkillHub

lay-summary-gen

v0.1.0

Converts complex medical abstracts into plain language summaries for

Sourced from ClawHub, Authored by ewankeynes

Installation

Please help me install the skill `lay-summary-gen` from SkillHub official store. npx skills add ewankeynes/lay-summary-gen

Lay Summary Gen

Generates plain-language summaries of medical research for non-expert audiences.

Features

  • Complex to simple language conversion
  • Jargon elimination
  • Reading level optimization (Grade 6-8)
  • Key takeaways extraction
  • EU CTR compliance support

Input Parameters

Parameter Type Required Description
abstract str Yes Original medical abstract
target_audience str No "patients", "public", "media"
max_words int No Maximum word count (default: 250)

Output Format

{
  "lay_summary": "string",
  "reading_level": "string",
  "key_takeaways": ["string"],
  "word_count": "int",
  "jargon_replaced": [{"term": "plain"}]
}

Risk Assessment

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

Security Checklist

  • [ ] No hardcoded credentials or API keys
  • [ ] No unauthorized file system access (../)
  • [ ] Output does not expose sensitive information
  • [ ] Prompt injection protections in place
  • [ ] Input file paths validated (no ../ traversal)
  • [ ] Output directory restricted to workspace
  • [ ] Script execution in sandboxed environment
  • [ ] Error messages sanitized (no stack traces exposed)
  • [ ] Dependencies audited

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