recommendations

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name: recommendations description: Generates actionable clinical advice (max 25 words) calibrated for patient skin tone using WebLLM or Gemini license: MIT compatibility: opencode metadata: audience: developers workflow: clinical-pipeline

What I do

I generate concise, actionable clinical recommendations based on the diagnosis, risk assessment, and web verification. I calibrate advice for the patient's specific skin tone and ensure recommendations are evidence-based.

When to use me

Use this when:

• Web verification is complete and you need clinical recommendations
• You need patient-appropriate, skin-tone-calibrated advice
• You're generating the final output for clinical decision support

Key Concepts

• 25 Word Limit: Concise recommendations for easy comprehension
• Skin-Tone Calibration: Advice appropriate for Fitzpatrick type
• Evidence-Based: Grounded in verified web sources
• recommendations_generated: State flag after generation complete

Source Files

• services/vision.ts: Recommendation generation
• types.ts: AnalysisResult with recommendations array

Code Patterns

• Synthesize diagnosis, risk, and web evidence
• Calibrate language for patient demographics
• Generate concise, actionable advice

Operational Constraints

• Maximum 25 words per recommendation
• Must be calibrated to Fitzpatrick type
• Must clearly differentiate AI reasoning from web-grounded advice