Abstract Trimmer

Compress academic abstracts to meet strict word limits while preserving key information, scientific accuracy, and readability. Supports multiple compression strategies for journal submissions, conference applications, and grant proposals.

Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.

Features

• Smart Compression: Multiple strategies (aggressive, conservative, balanced)
• Key Information Preservation: Retains critical findings and statistics
• Structural Integrity: Maintains Background-Methods-Results-Conclusion flow
• Quantitative Safety: Protects numbers, P-values, and confidence intervals
• Batch Processing: Trim multiple abstracts efficiently
• Quality Validation: Post-trim readability and accuracy checks

Usage

Basic Usage

bash

# Trim abstract from file
python scripts/main.py --input abstract.txt --target 250

# Trim abstract from command line
python scripts/main.py --text "Your abstract here..." --target 200

# Check word count only
python scripts/main.py --input abstract.txt --target 250 --check-only

Parameters

Parameter	Type	Default	Required	Description
--input, -i	str	None	No	Input file containing abstract
--text, -t	str	None	No	Abstract text (alternative to --input)
--target, -T	int	250	No	Target word count
--strategy, -s	str	balanced	No	Trimming strategy (conservative/balanced/aggressive)
--output, -o	str	None	No	Output file path
--check-only, -c	flag	False	No	Only check word count without trimming
--format	str	json	No	Output format (json/text)

Advanced Usage

bash

# Aggressive trimming with text output
python scripts/main.py \
  --input abstract.txt \
  --target 200 \
  --strategy aggressive \
  --format text \
  --output trimmed.txt

# Batch check multiple abstracts
for file in *.txt; do
  python scripts/main.py --input "$file" --target 250 --check-only
done

Trimming Strategies

Strategy	Approach	Best For
Conservative	Remove filler words, simplify sentences	Minor trims (10-20 words)
Balanced	Condense phrases, merge sentences	Moderate trims (20-50 words)
Aggressive	Remove secondary details, abbreviate	Major trims (50+ words)

Output Format

JSON Output

json

{
  "trimmed_abstract": "Compressed abstract text...",
  "original_words": 320,
  "final_words": 248,
  "reduction_percent": 22.5
}

Text Output

text

Compressed abstract text...

Technical Difficulty: LOW

⚠️ AI自主验收状态: 需人工检查

This skill requires:

• Python 3.7+ environment
• No external dependencies

Dependencies

Required Python Packages

bash

pip install -r requirements.txt

Requirements File

No external dependencies required (uses only Python standard library).

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python scripts executed locally	Low
Network Access	No network access	Low
File System Access	Read/write text files only	Low
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	No sensitive data exposure	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
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized
• Dependencies audited

Prerequisites

bash

# No dependencies required
python scripts/main.py --help

Evaluation Criteria

Success Metrics

• Successfully trims abstracts to target word count
• Preserves key scientific information
• Maintains grammatical correctness
• Handles edge cases gracefully

Test Cases

1. Basic Trimming: Input abstract → Trimed to target word count
2. Check Mode: --check-only flag → Reports word count statistics
3. File I/O: Read from file, write to file → Correct file handling
4. Different Strategies: All three strategies work → Different compression levels

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-15
• Known Issues: None
• Planned Improvements:
  • Enhanced protection for quantitative data
  • Support for structured abstracts
  • Batch processing mode

References

See references/ for:

• Compression strategies documentation
• Protected elements guidelines
• Journal word limits by publisher

Limitations

• Language: Optimized for English academic abstracts
• Content Type: Designed for structured abstracts (BMRC format)
• No Rewriting: Only removes/compresses; doesn't rephrase
• Final Review: Automated trimming requires human validation

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✂️ Remember: This tool helps meet word limits, but never sacrifice scientific accuracy. Always validate that trimmed abstracts maintain the integrity of your findings.