Troubleshooting Protocol Generation
Sometimes PraxPilot may generate a protocol with limited recommendations or leave certain phases empty. This usually happens when the system does not detect enough meaningful clinical information in the case data.
Below are the most common reasons and how to resolve them.
1. Insufficient Case Information
PraxPilot generates protocols based on clinical signals detected in the case intake.
If the case contains very little information, the system may not have enough context to generate recommendations.
Examples of limited input:
Very short notes
Missing symptom descriptions
No lab markers or clinical observations
Generic statements like “patient feels unwell”
How to improve results
Provide more structured information such as:
Primary complaint
Symptom patterns
Duration of symptoms
Relevant lab findings
Practitioner observations
The more clinically relevant context you provide, the more useful the generated protocol will be.
2. Placeholder or Test Data
If the case contains placeholder text such as:
“Lorem ipsum”
Random characters
Test notes
Non-clinical text
PraxPilot may intentionally return minimal or empty recommendations.
This safeguard helps prevent the system from generating clinical recommendations based on meaningless or non-clinical input.
3. Missing Lab Context
Lab markers can provide important signals for protocol generation.
If no labs are provided, PraxPilot can still generate protocols based on symptoms and notes, but the recommendations may be more conservative.
You can improve results by including:
Relevant biomarkers
Reference ranges if available
Practitioner interpretation of labs
4. Sections May Be Left Empty Intentionally
In some cases, PraxPilot may leave Phase 2 or Phase 3 empty.
This happens when:
The system does not detect enough signals to justify later-stage interventions
The clinical context suggests a conservative initial approach
The case data is too limited for multi-phase recommendations
This behavior is intentional and helps avoid unnecessary or speculative recommendations.
5. You Can Always Edit the Protocol
Remember that PraxPilot is designed to assist practitioners — not replace clinical judgment.
You can always:
Add supplements manually
Edit diet or lifestyle recommendations
Adjust dosing or protocols
Use Write with AI to refine specific sections
6. Regenerating a Section
If you want additional ideas or adjustments, you can regenerate specific sections.
Use Write with AI inside a phase to:
Expand recommendations
Adjust clinical focus
Generate alternative approaches
This allows you to refine the protocol while maintaining full clinical control.
Best Practices for Reliable Protocol Generation
For the best results:
Include meaningful clinical context
Provide symptoms and relevant labs
Avoid placeholder or test text
Review extracted data before generating
High-quality case information leads to more accurate and useful protocol suggestions.