From ai-brain-starter
Scans years of HealthKit and journal data to surface strong multi-year correlations (Briden noise filter). Reports top signals, Floor-body fingerprints, sleep trends, longitudinal markers, and symptom correlates.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ai-brain-starter:longitudinal [scope -- e.g. 'all', '5y', '1y', leave blank for 1y default][scope -- e.g. 'all', '5y', '1y', leave blank for 1y default]The summary Claude sees in its skill listing — used to decide when to auto-load this skill
When the user types /longitudinal, run the multi-year correlation pass and surface only the strongest signals across years of health-mcp + journal data.
When the user types /longitudinal, run the multi-year correlation pass and surface only the strongest signals across years of health-mcp + journal data.
Generate the report in the language the user writes in. If Spanish, all sections including the panel commentary are in Spanish.
Parse the argument for window:
all -> earliest record in DB to todayNy -> last N years (e.g. 5y, 3y)Nm -> last N months (e.g. 18m)If all, query the DB for the earliest record date first:
SELECT MIN(start_date) FROM records WHERE value IS NOT NULL
Always call health_top_signals(vault_root=..., lookback_days=N, min_strength="moderate") first. This is Lara Briden's dissent codified: most correlations are noise. The substrate has already filtered. Start with what's left.
If signal_count == 0, report "no signals above noise threshold for this window" and stop — do not invent. Surface what IS there: the deltas and r-values that didn't quite clear the threshold, in case the user wants to relax it.
Load the journal index, count Floors in the window, take the top 3 by occurrence.
For each Floor, call:
health_floor_body_fingerprint(floor=<name>, vault_root=..., lookback_days=N)
Report the body fingerprint deltas (HRV, RHR, sleep efficiency, cycle phase distribution). If delta_pct exceeds ±10% AND n_on_floor >= 10, this is a real fingerprint. Below that, mention it but flag as "weak."
Call health_sleep_architecture(start, end) for the window AND for the prior matching window (e.g. 1y now vs 1y prior). Compare REM%, Deep%, Core%, efficiency. Flag drift > 5 percentage points.
Call health_longitudinal_summary(start, end, granularity="quarter"). Pull HRV baseline, VO2max, lean body mass, walking steadiness, sleep efficiency by quarter. Compute trend slope per marker (rough linear regression: (last - first) / first * 100).
Surface only markers with > 5% drift across the window.
Call health_symptom_correlate(symptom_type=None, vault_root=..., lookback_days=N). If any symptom has > 15% delta_pct on a body metric AND n >= 5 days with the symptom, surface it.
If [VAULT_PATH]/Meta/Patterns/loops-detected.json exists (created by /patterns), read it. For each named loop with date list, call health_loop_signature(loop_dates_iso=[...], vault_root=...). Surface the loop body fingerprint.
If the file doesn't exist, skip this step silently — no error.
## Longitudinal pattern review -- <window>
### What survived the noise filter
<bullet list of top_signals results, strongest first>
### Floor x body fingerprint
<for each top 3 Floor: name, occurrence count, body deltas with > 10% threshold>
### Sleep architecture
<current vs prior window comparison, flag drift>
### Longevity markers (per quarter)
<table or bullets of HRV baseline, VO2max, lean mass trend>
### Symptoms
<symptom correlates with > 15% delta>
### Named loops (if /patterns ran recently)
<loop body fingerprints>
### Health panel commentary
<3-5 voices from the Health & Body section of advisory-panel.md commenting on the strongest signals. Required: Peter Attia (longevity), Stacy Sims (cycle phase if any female-physiology pattern is present), Bessel van der Kolk (HRV-vagal-tone if Floor x body signal is strong), Lara Briden (dissent: did we pick signal or noise). Each voice: 1-2 sentences referencing a SPECIFIC number from the report.>
### What to do next
<3-5 concrete, action-shaped items based on the strongest signals. NOT "consider X" -- "do X this week.">
Every number in the report comes from a health-mcp tool call. If a tool returns error, surface the error verbatim and skip that section. Never invent a metric. Never round so heavily that a 38.2 ms HRV becomes "around 40."
If the lookback window includes a period before the user started recording (e.g. they ran /longitudinal all but the DB only has 3 years), report the actual span you found: "earliest record: 2023-04-12, so the window is 2023-04-12 to 2026-05-10 (3.1 years)."
If a single marker shows > 25% drift in the wrong direction (HRV baseline dropping > 25%, VO2max dropping > 25%, lean mass dropping > 10%), surface it AT THE TOP of the report with the marker name in bold and a one-line note. These are health-significant changes worth flagging directly. Do not bury them in section 4.
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