Lay Press Release Writer

Metadata

• ID: 144
• Name: Lay Press Release Writer
• Description: Transform academic papers into university press center style press releases
• Version: 1.0.0
• Author: OpenClaw
• Entry Point: scripts/main.py

Purpose

Transforms complex academic papers into press releases for general audiences, alumni, and media. Maintains scientific accuracy while conveying research highlights and value in accessible language.

Capabilities

• Extracts core findings and innovation points from papers
• Generates press releases in university press center style
• Adds compelling headlines and leads
• Provides researcher quotes
• Includes relevant background information

Input Parameters

Output Format

Returns JSON format:

{
  "headline": "Compelling Headline",
  "subheadline": "Subheadline",
  "dateline": "Location, Date",
  "lead": "Lead paragraph",
  "body": "Body content",
  "quotes": ["Researcher quote 1", "Researcher quote 2"],
  "boilerplate": "Institution introduction",
  "media_contact": "Media contact information"
}

Usage

python scripts/main.py --paper-text "Paper content..." --institution "XX University"

Dependencies

• Python 3.8+
• Dependencies see requirements.txt

Examples

Example 1: Basic Usage

python scripts/main.py \
  --paper-text "..." \
  --paper-title "New Breakthrough in Quantum Computing" \
  --institution "Tsinghua University" \
  --authors "Zhang San,Li Si"

Notes

• Generated content should maintain scientific accuracy
• Avoid oversimplification that leads to misunderstanding
• Highlight practical application value of research
• Comply with standard press release structure (inverted pyramid structure)

Risk Assessment

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

# 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