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turnnoblindeye

Wellness Project MCP

log_wearable

Logs or updates daily health metrics like heart rate, HRV, steps, blood pressure, glucose, and temperature for a specified date, handling corrections and manual entries.

Instructions

Log daily wearable/manual health metrics (RHR, HRV, Zone Minutes / AZM, VO2max, calories eaten / dietary energy, stress, supplemental steps, and physiological vitals including SpO₂, respiratory rate, skin temperature, blood pressure, blood glucose, and core temperature).

VITALS — use the vital fields for manual/home/device readings and corrections, including a finger-stick, CGM, home glucose meter, or wearable/Apple Health/Health Connect value the user explicitly wants stored manually. A glucose value from an actual lab report or blood draw belongs in log_lab_results instead, not here.

STEPS — read before using step_count: manual step_count is ADDITIVE — it adds on top of whatever a connected wearable (Fitbit, Oura, Apple Health, Health Connect) already recorded that day; it never replaces or overrides device data. Only use it when the user explicitly says they walked steps their device did NOT capture (phone left home, battery died, device not worn). If the user says sync is wrong, steps look doubled, or they want to fix/override/replace device data: do NOT pass step_count — explain that manual steps add on top, and sync issues need investigating at the device level.

ALL OTHER FIELDS (RHR, HRV, AZM, VO2max, stress, and physiological vitals) replace the existing manual value for that day and are safe to use for corrections.

INFER — do not ask: date defaults to today unless the user says otherwise.

IDEMPOTENT: if the values you'd log already exist for that date (any source), the tool returns a no-op success — report this as "already had data", not "failed".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesDate for the entry. Format: YYYY-MM-DD. Default to today.
resting_hrNoResting heart rate in BPM. Optional.
step_countNoSupplemental steps NOT captured by any connected wearable. ADDITIVE — adds to device data, never replaces it. Only use when user explicitly says their device missed these steps.
hrv_morningNoMorning HRV in milliseconds (RMSSD or similar). Optional.
skin_temp_cNoSkin temperature in °C. Manual/home/device reading. Optional.
spo2_avg_pctNoSpO₂ in %. Manual/home/device reading. Optional.
stress_scoreNoStress score (0–100 scale). Optional.
vo2max_estimateNoVO2max estimate (ml/kg/min). Optional.
core_body_temp_cNoCore temperature in °C. Manual/home/device reading. Optional.
dietary_caloriesNoDietary energy / calories eaten for the day in kcal, imported from a connected health app (Apple Health / Health Connect). Optional.
systolic_bp_mm_hgNoSystolic blood pressure in mmHg. Provide with diastolic_bp_mm_hg. Manual/home/device reading. Optional.
diastolic_bp_mm_hgNoDiastolic blood pressure in mmHg. Provide with systolic_bp_mm_hg. Manual/home/device reading. Optional.
blood_glucose_mg_dlNoBlood glucose in mg/dL. Manual/home/device reading. Optional.
active_zone_min_peakNoZone Minutes (also called Active Zone Minutes by Fitbit, Heart Points by Google Fit) at peak intensity. Optional.
confirm_supplementalNoSet to true ONLY after the user has explicitly confirmed these steps were walked without their device and were not captured. Do not set true based on your own inference.
respiratory_rate_bpmNoBreathing in br/min. Manual/home/device reading. Optional.
active_zone_min_moderateNoZone Minutes (also called Active Zone Minutes by Fitbit, Heart Points by Google Fit) at moderate intensity. Optional.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesHuman-readable result text returned by the tool.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.1

TDQS

A4/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description is highly transparent (additive step semantics, replacement behavior, no-op success), but it explicitly claims 'IDEMPOTENT' while the annotation idempotentHint is false. This is a direct annotation contradiction, so per rubric the score must be 1 despite the otherwise rich detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well structured, with front-loaded purpose and uppercase section headers (VITALS, STEPS, ALL OTHER FIELDS, INFER, IDEMPOTENT). Some enumeration of vitals duplicates the schema, creating mild redundancy, but the operational rules justify most of the length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 17-parameter tool with an output schema and 100% schema coverage, the description covers all critical behaviors: defaulting to today, step additive semantics, replacement scope, no-op idempotent success, and lab-result routing. Only minor gaps exist, such as explicit behavior for omitting all fields, but nothing required for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds substantial extra meaning: step_count is additive and requires explicit confirmation, vitals replace existing manual values, systolic requires diastolic to accompany, and glucose routing depends on source. These are the exact semantic constraints the schema does not fully capture.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies a specific verb and resource: logging daily wearable/manual health metrics across many vitals. It explicitly distinguishes where lab glucose values belong (log_lab_results instead), which separates it from that sibling without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use and when-not-to-use guidance: manual step_count only for device-missed steps, never for sync issues; lab-derived glucose belongs in log_lab_results; all other fields replace existing manual values. This is model-level routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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