Agent skill
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.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/abstract-trimmer
SKILL.md
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
| 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
# 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
{
"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 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
# 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
- Basic Trimming: Input abstract → Trimed to target word count
- Check Mode: --check-only flag → Reports word count statistics
- File I/O: Read from file, write to file → Correct file handling
- 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.
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