conflict-of-interest-checker
# Conflict of Interest Checker
Reviewer conflict detection tool.
## Use Cases
- Journal submission prep
- Editorial decisions
- Peer review integrity
- Compliance verification
## Parameters
| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--authors`, `-a` | string | - | Yes | Comma-separated author names |
| `--reviewers`, `-r` | string | - | Yes | Comma-separated reviewer names |
| `--publications`, `-p` | string | - | No | CSV file with publication records |
### CSV Format
```csv
author,reviewer,paper_id
Smith,Brown,paper1
Smith,Jones,paper2
```
## Usage
```bash
# Check with demo data
python scripts/main.py --authors "Smith,Jones,Lee" --reviewers "Brown,Davis,Wilson"
# Check with publication records
python scripts/main.py --authors "Smith,Jones" --reviewers "Brown,Davis" --publications pubs.csv
```
## Returns
- Conflict flagging (coauthorship, institutional)
- Shared publication list
- Recommendation: Accept/Recuse
- Alternative reviewer suggestions
### Example Output
```
⚠ Found 2 potential conflict(s):
1. COAUTHORSHIP CONFLICT
Reviewer: Brown
Author: Smith
Shared papers: paper1
2. COAUTHORSHIP CONFLICT
Reviewer: Wilson
Author: Smith
Shared papers: paper2
```
## 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
- Additional feature support
标签
skill
ai