IHC/IF Optimizer
Immunostaining protocol optimization.
Use Cases
- Brain tissue staining
- Liver antigen retrieval
- Antibody dilution optimization
- Fluorescence panel design
Parameters
| Parameter | Type | Default | Required | Description |
|---|
| ----------- | ------ | --------- | ---------- | ------------- |
--tissue-type | string | - | Yes | Tissue type (Brain, Liver, Kidney, etc.) |
--antigen | string | - | Yes | Target protein/antigen name |
--detection-method | string | IHC | No | Detection method (IHC or IF) |
--output, -o | string | stdout | No | Output file path |
--format | string | text | No | Output format (text, json, markdown) |
Returns
- Recommended retrieval method
- Antibody dilutions
- Blocking conditions
- Counterstain suggestions
Example
Brain tissue + Phospho-protein → Citrate retrieval, 1:200 antibody
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