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.

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Install skill "abstract-trimmer" with this command: npx skills add aipoch-ai/abstract-trimmer

Abstract Trimmer

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

# 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

ParameterTypeDefaultRequiredDescription
--input, -istrNoneNoInput file containing abstract
--text, -tstrNoneNoAbstract text (alternative to --input)
--target, -Tint250NoTarget word count
--strategy, -sstrbalancedNoTrimming strategy (conservative/balanced/aggressive)
--output, -ostrNoneNoOutput file path
--check-only, -cflagFalseNoOnly check word count without trimming
--formatstrjsonNoOutput format (json/text)

Advanced Usage

# 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

StrategyApproachBest For
ConservativeRemove filler words, simplify sentencesMinor trims (10-20 words)
BalancedCondense phrases, merge sentencesModerate trims (20-50 words)
AggressiveRemove secondary details, abbreviateMajor trims (50+ words)

Output Format

JSON Output

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

Text Output

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

pip install -r requirements.txt

Requirements File

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

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython scripts executed locallyLow
Network AccessNo network accessLow
File System AccessRead/write text files onlyLow
Instruction TamperingStandard prompt guidelinesLow
Data ExposureNo sensitive data exposureLow

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

# 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

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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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