Analyze Symptoms

Digestive symptoms typically appear 24-48 hours after consuming a trigger food, though some reactions (especially to FODMAPs) can be faster (6-24 hours). For each symptom entry, look at all meals eaten in the preceding 48 hours.

The user tracks three symptom categories:

1. Bristol Scale (1-7): Gut health. 3-4 is ideal. 5-7 suggests diarrhea-type issues (IBS-D pattern). 1-2 suggests constipation.
2. Eczema (0-3): Skin inflammation. 0 is clear, 3 is severe. Location matters.
3. Ears (0-3): Itchiness, fullness, irritation. 0 is fine, 3 is infected.

Workflow

1. Read and Parse the Symptom Log

Read memory/symptom_log.md and extract all entries. For each entry, note:

• Date and time
• Bristol scale score
• Eczema score and location
• Ear score
• Meals listed in the preceding 24-48 hours
• Any contextual notes (stress, sleep, etc.)

If the log has few entries (less than 2 weeks), tell the user that more data will improve the analysis and show what patterns you can see so far.

2. Cross-Reference with Meal Plans

The symptom log should list meals consumed, but cross-reference with memory/weeks/*/meals.md to fill in gaps or verify. Break each meal down to its individual ingredients using recipe files.

3. Build an Ingredient Frequency Table

For each symptom event (Bristol > 4, eczema > 0, ears > 0), list every ingredient consumed in the 48 hours prior. Then count how often each ingredient appears before symptom events vs. symptom-free periods.

Present this as a table:

The correlation score is a simple ratio — higher means the ingredient appears disproportionately before symptoms. This isn't statistical proof, but it highlights candidates for elimination testing.

4. Look for Patterns

Beyond individual ingredients, look for:

• Timing patterns: Do symptoms cluster on certain days of the week? After certain meal types (heavy vs. light)?
• Combination effects: Do symptoms appear when two specific ingredients are eaten together but not separately?
• Dose effects: Do larger portions of a food correlate more strongly than small amounts?
• FODMAP categories: If the user is doing FODMAP testing, group ingredients by FODMAP type (fructans, GOS, polyols, etc.) and check if an entire category correlates
• Non-food factors: Note if stress, poor sleep, or other contextual factors appear alongside symptoms
• Cross-symptom patterns: Do gut symptoms, eczema, and ear issues flare together (suggesting systemic inflammation) or independently?

5. Present Findings

Structure the analysis as:

1. Summary: How many entries analyzed, date range, overall symptom frequency
2. Top Correlations: The 3-5 ingredients or food categories with strongest correlation to symptoms
3. Pattern Observations: Timing patterns, combination effects, non-food factors
4. FODMAP Alignment: How findings relate to known FODMAP categories (reference fodmap_plan.md)
5. Recommended Next Steps: Specific elimination tests to run, ordered by strength of evidence
6. Confidence Assessment: How much data supports these observations and what would strengthen the analysis

6. Important Boundaries

• Frame everything as "the data suggests" or "this pattern is worth investigating," never "X is causing your symptoms"
• Don't diagnose conditions. Suggest seeing a healthcare provider for clinical concerns
• Distinguish between observations (what the data shows) and hypotheses (what you'd test next)
• If the data is sparse, say so clearly rather than over-interpreting
• Acknowledge confounders — stress, sleep, and other non-food factors can drive symptoms too