comparison-table-gen
Auto-generates comparison tables for concepts, drugs, or study results in Markdown format.
Best use case
comparison-table-gen is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Auto-generates comparison tables for concepts, drugs, or study results in Markdown format.
Teams using comparison-table-gen should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/comparison-table-gen/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How comparison-table-gen Compares
| Feature / Agent | comparison-table-gen | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Auto-generates comparison tables for concepts, drugs, or study results in Markdown format.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Comparison Table Gen
Generates comparison tables for medical content.
## Features
- Side-by-side comparisons
- Markdown table output
- Drug comparison templates
- Study result comparisons
## Parameters
| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--items`, `-i` | string | - | Yes | Items to compare (comma-separated) |
| `--attributes`, `-a` | string | - | Yes | Comparison attributes (comma-separated) |
| `--output`, `-o` | string | - | No | Output JSON file path |
## Usage
```bash
# Compare two drugs
python scripts/main.py --items "Drug A,Drug B" --attributes "Mechanism,Dose,Side Effects"
# Save to file
python scripts/main.py --items "Surgery,Chemo,Radiation" --attributes "Cost,Efficacy" --output comparison.json
```
## Input Format
- **items**: Comma-separated list of items to compare (e.g., "Drug A,Drug B")
- **attributes**: Comma-separated list of comparison attributes (e.g., "Mechanism,Dose")
## Output Format
```json
{
"markdown_table": "string",
"html_table": "string"
}
```
## 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
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