- name
- serial-dilution-calculator
- description
- Generate qPCR/ELISA dilution protocols with precise pipetting steps
- version
- 1.0.0
- category
- Wet Lab
- tags
- []
- author
- AIPOCH
- license
- MIT
- status
- Draft
- risk_level
- Medium
- skill_type
- Tool/Script
- owner
- AIPOCH
- reviewer
- last_updated
- 2026-02-06
Serial Dilution Calculator
Step-by-step dilution protocol generator.
Use Cases
- qPCR standard curves
- ELISA plate setup
- Drug dose responses
- MIC determinations
Parameters
starting_conc: Stock concentrationfinal_conc: Target concentrationdilution_factor: Step dilutiontotal_volume: Per well volume
Returns
- Pipetting scheme table
- Required volumes
- Plate layout suggestion
- Common pitfall warnings
Example
"Take 10uL stock + 90uL diluent for 1:10..."
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
- Basic Functionality: Standard input → Expected output
- Edge Case: Invalid input → Graceful error handling
- 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