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gevety

Access your Gevety health data - biomarkers, healthspan scores, biological age, supplements, activities, daily actions, 90-day health protocol, and upcoming tests

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Kernel8901/ai-agent-skills-classification
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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
gevety
version
1.5.0
description
Access your Gevety health data - biomarkers, healthspan scores, biological age, supplements, activities, daily actions, 90-day health protocol, and upcoming tests
homepage
https://gevety.com
user-invocable
true
command
gevety
metadata
{"clawdbot":{"primaryEnv":"GEVETY_API_TOKEN","requires":{"env":"[Truncated]"}}}
# Gevety Health Assistant You have access to the user's health data from Gevety via the REST API. Use `web_fetch` to retrieve their biomarkers, healthspan scores, and wearable statistics. ## First-Time Setup If this is the user's first time using Gevety, guide them through setup: 1. **Get a Gevety account**: Sign up at https://gevety.com if they don't have one 2. **Upload blood tests**: They need to upload lab reports to have biomarker data 3. **Generate an API token**: - Go to https://gevety.com/settings - Click "Developer API" tab - Click "Generate Token" - Copy the token (starts with `gvt_`) 4. **Configure Clawdbot**: Add the token to `~/.clawdbot/clawdbot.json`: ```json { "skills": { "entries": { "gevety": { "apiKey": "gvt_your_token_here" } } } } ``` After adding the token, they'll need to restart Clawdbot for changes to take effect. ## Authentication All requests require Bearer authentication. Use the `GEVETY_API_TOKEN` environment variable: ``` Authorization: Bearer $GEVETY_API_TOKEN ``` Base URL: `https://api.gevety.com` ## Biomarker Name Handling The API preserves biomarker specificity. Fasting and non-fasting variants are distinct: | Input Name | API Returns | Notes | |------------|-------------|-------| | CRP, C-Reactive Protein | **CRP** or **C-Reactive Protein** | Standard CRP (LOINC 1988-5) | | hsCRP, hscrp, Cardio CRP | **hs-CRP** | High-sensitivity CRP (LOINC 30522-7) | | Glucose, Blood Glucose | **Glucose** | Generic/unspecified glucose | | Fasting Glucose, FBS, FBG | **Glucose Fasting** | Fasting-specific glucose | | Insulin, Serum Insulin | **Insulin** | Generic/unspecified insulin | | Fasting Insulin | **Insulin Fasting** | Fasting-specific insulin | | IG | **Immature Granulocytes** | Expanded for clarity | | Vitamin D, 25-OH Vitamin D | **Vitamin D** | | | LDL, LDL Cholesterol | **LDL Cholesterol** | | **Important**: The API no longer forces fasting assumptions. If a lab report says "Glucose" without specifying fasting, it returns as "Glucose" (not "Fasting Glucose"). This preserves the original context from your lab results. ## Available Endpoints ### 1. List Available Data (Start Here) **Always call this first** to discover what health data exists. ``` GET /api/v1/mcp/tools/list_available_data ``` Returns: - `biomarkers`: List of tracked biomarkers with test counts and latest dates - `wearables`: Connected devices and available metrics - `insights`: Whether healthspan score is calculated, axis scores available - `data_coverage`: Percentage of recommended biomarkers tracked (0-100) ### 2. Get Health Summary Overview of the user's health status. ``` GET /api/v1/mcp/tools/get_health_summary ``` Returns: - `overall_score`: Healthspan score (0-100) - `overall_status`: OPTIMAL, GOOD, SUBOPTIMAL, or NEEDS_ATTENTION - `trend`: IMPROVING, STABLE, or DECLINING - `axis_scores`: Scores for each health dimension (metabolic, cardiovascular, etc.) - `top_concerns`: Biomarkers needing attention - `scoring_note`: Explanation when overall score differs from axis scores (e.g., "Overall healthspan is high, but Inflammation axis needs attention") **Note on scores**: The overall healthspan score is a weighted composite. It's possible to have a high overall score while one axis is low (or vice versa). The `scoring_note` field explains these situations. ### 3. Query Biomarker Get detailed history for a specific biomarker. ``` GET /api/v1/mcp/tools/query_biomarker?biomarker={name}&days={days} ``` Parameters: - `biomarker` (required): Name or alias (e.g., "vitamin d", "ldl", "hba1c", "crp") - `days` (optional): History period, 1-730, default 365 Returns: - `canonical_name`: Standardized biomarker name (see table above) - `history`: Array of test results with dates, values, units, flags - `latest`: Most recent result - `trend`: Direction (IMPROVING, STABLE, DECLINING) and percent change - `optimal_range`: Evidence-based optimal values **Tip**: If biomarker not found, the response includes `did_you_mean` suggestions. ### 4. Get Wearable Stats Daily metrics from connected wearables (Garmin, Oura, Whoop, etc.). ``` GET /api/v1/mcp/tools/get_wearable_stats?days={days}&metric={metric} ``` Parameters: - `days` (optional): History period, 1-90, default 30 - `metric` (optional): Focus on specific metric (steps, hrv, sleep, etc.) Returns: - `connected_sources`: List of connected wearable platforms - `daily_metrics`: Per-day data (steps, resting HR, HRV, sleep, recovery) - `summaries`: Aggregated stats with averages, min, max, trends ### 5. Get Opportunities Get ranked health improvement opportunities with estimated healthspan impact. ``` GET /api/v1/mcp/tools/get_opportunities?limit={limit}&axis={axis} ``` Parameters: - `limit` (optional): Max opportunities to return, 1-50, default 10 - `axis` (optional): Filter by health axis (metabolic, cardiovascular, etc.) Returns: - `opportunities`: Ranked list of improvement opportunities - `total_opportunity_score`: Total healthspan points available - `total_years_estimate`: Estimated years of healthy life if all optimized - `healthspan_score`: Current healthspan score Each opportunity includes: - `biomarker`: Standardized biomarker name - `current_value` / `optimal_value`: Where you are vs target - `opportunity_score`: Healthspan points gained if optimized - `years_estimate`: Estimated healthy years gained - `priority`: Rank (1 = highest impact) ### 6. Get Biological Age Calculate biological age using validated algorithms (PhenoAge, Light BioAge). ``` GET /api/v1/mcp/tools/get_biological_age ``` Returns: - `result`: Biological age calculation (if available) - `biological_age`: Calculated biological age - `chronological_age`: Calendar age - `age_acceleration`: Difference (positive = aging faster) - `algorithm`: Which algorithm was used - `biomarkers_used`: Biomarkers that contributed - `interpretation`: What the result means - `available`: Whether calculation was possible - `reason`: Why not available (if applicable) - `upgrade_available`: Can unlock better algorithm with more data - `upgrade_message`: What additional tests would help ### 7. List Supplements Get the user's supplement stack. ``` GET /api/v1/mcp/tools/list_supplements?active_only={true|false} ``` Parameters: - `active_only` (optional): Only show currently active supplements, default false Returns: - `supplements`: List of supplements with dosage, frequency, duration - `active_count`: Number of currently active supplements - `total_count`: Total supplements tracked Each supplement includes: - `name`: Supplement name - `dose_text`: Formatted dosage (e.g., "1000 mg daily", "200mg EPA + 100mg DHA daily") - `is_active`: Currently taking - `duration_days`: How long on this supplement **Note**: For multi-component supplements (like fish oil), `dose_text` shows all components (e.g., "200mg EPA + 100mg DHA daily"). ### 8. Get Activities Get workout/activity history from connected wearables. ``` GET /api/v1/mcp/tools/get_activities?days={days}&activity_type={type} ``` Parameters: - `days` (optional): History period, 1-90, default 30 - `activity_type` (optional): Filter by type (running, cycling, strength, etc.) Returns: - `activities`: List of workouts with metrics - `total_count`: Number of activities - `total_duration_minutes`: Total workout time - `total_distance_km`: Total distance covered - `total_calories`: Total calories burned Each activity includes: - `activity_type`: Type (running, cycling, swimming, etc.) - `name`: Activity name - `start_time`: When it started - `duration_minutes`: How long - `distance_km`: Distance (if applicable) - `calories`: Calories burned - `avg_hr` / `max_hr`: Heart rate data - `source`: Where the data came from (garmin, strava, etc.) ### 9. Get Today's Actions Get the user's action checklist for today. ``` GET /api/v1/mcp/tools/get_today_actions?timezone={timezone} ``` Parameters: - `timezone` (optional): IANA timezone (e.g., "America/New_York"), default UTC Returns: - `effective_date`: The date being queried in user's timezone - `timezone`: Timezone used for calculation - `window_start` / `window_end`: Day boundaries (ISO datetime) - `actions`: List of today's actions - `completed_count` / `total_count`: Completion stats - `completion_pct`: Numeric completion percentage (0-100) - `last_updated_at`: Cache staleness indicator Each action includes: - `action_id`: Stable ID for deep-linking - `title`: Action title - `action_type`: Type (supplement, habit, diet, medication, test, procedure) - `completed`: Whether completed today - `scheduled_window`: Time window (morning, afternoon, evening, any) - `dose_text`: Dosage info if applicable (e.g., "1000 mg daily") ### 10. Get Protocol Get the user's 90-day health protocol with top priorities. ``` GET /api/v1/mcp/tools/get_protocol ``` Returns: - `protocol_id`: Stable protocol ID - `phase`: Current phase (week1, month1, month3) - `days_remaining`: Days until protocol expires - `generated_at` / `last_updated_at`: Timestamps - `top_priorities`: Top 5 health priorities with reasoning - `key_recommendations`: Diet and lifestyle action items - `total_actions`: Total actions in protocol Each priority includes: - `priority_id`: Stable ID (same as rank) - `rank`: Priority rank (1 = highest) - `biomarker`: Standardized biomarker name - `status`: Current status (critical, concerning, suboptimal, optimal) - `target`: Target value with unit - `current_value` / `unit`: Current measured value - `measured_at`: When this biomarker was last measured - `why_prioritized`: Explanation for why this is prioritized **Note**: If no protocol exists, returns a helpful error with suggestion to generate one at gevety.com/protocol. ### 11. Get Upcoming Tests Get tests that are due or recommended based on biomarker history and AI recommendations. ``` GET /api/v1/mcp/tools/get_upcoming_tests ``` Returns: - `tests`: List of upcoming tests sorted by urgency - `overdue_count`: Number of overdue tests - `due_soon_count`: Tests due within 30 days - `recommended_count`: AI-recommended tests - `total_count`: Total number of upcoming tests Each test includes: - `test_id`: Stable ID for deep-linking (format: `panel_{id}` or `recommended_{id}`) - `name`: Test or panel name - `test_type`: Type (panel, biomarker, recommended) - `urgency`: Priority level (overdue, due_soon, recommended) - `due_reason`: Why this test is needed (e.g., "Due 2 weeks ago", "AI recommendation") - `last_tested_at`: When this was last tested (if applicable) - `biomarkers`: List of biomarkers included (for panels) ## Interpreting Scores ### Healthspan Score (0-100) | Range | Status | Meaning | |-------|--------|---------| | 80-100 | OPTIMAL | Excellent health optimization | | 65-79 | GOOD | Above average, minor improvements possible | | 50-64 | SUBOPTIMAL | Room for improvement | | <50 | NEEDS_ATTENTION | Several areas need focus | ### Axis Scores Each health dimension is scored independently: - **Metabolic**: Blood sugar, insulin, lipids - **Cardiovascular**: Heart health markers - **Inflammatory**: hs-CRP, homocysteine - **Hormonal**: Thyroid, testosterone, cortisol - **Nutritional**: Vitamins, minerals - **Liver/Kidney**: Organ function markers **Important**: It's possible to have a high overall score with one low axis score (or vice versa). The `scoring_note` field in `get_health_summary` explains these situations. ### Biomarker Status Labels | Label | Meaning | |-------|---------| | OPTIMAL | Within evidence-based ideal range | | NORMAL | Within lab reference range | | SUBOPTIMAL | Room for improvement | | HIGH/LOW | Outside lab reference range | | CRITICAL | Needs immediate medical attention | ## Common Workflows ### "How am I doing?" 1. Call `list_available_data` to see what's tracked 2. Call `get_health_summary` for the overall picture 3. Highlight top concerns and recent trends 4. If `scoring_note` is present, explain the score discordance ### "Tell me about my vitamin D" 1. Call `query_biomarker?biomarker=vitamin d` 2. Present history, current status, and trend 3. Note optimal range vs current value ### "What's my CRP?" / "How's my inflammation?" 1. Call `query_biomarker?biomarker=crp` (returns as "CRP" or "hs-CRP" depending on lab) 2. Present the value and trend 3. Explain what CRP measures (inflammation marker) - note if it's high-sensitivity
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