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MetricBridge (formerly Health Export AI)

MetricBridge (formerly Health Export AI)

by PhilipAD
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

resolve_metric

Read-onlyIdempotent

Look up any metric spelling, alias, or HealthKit identifier to get its canonical name, unit, and conversion; convert one value and flag ambiguous or mismatched measures.

Instructions

Look a metric name up in the canonical naming and unit table. Accepts the export's own name (step_count), a HealthKit identifier (StepCount, HKQuantityTypeIdentifierStepCount), a display title (Step Count) or a common alias (steps, hrv, spo2, weight) and returns the canonical metric, its unit (percentages are 0 to 1 fractions), the unit variants other apps use with the exact formula into the canonical unit, and whether this export holds it. Pass {value, unit} to convert one value, e.g. 180 lb to kg. A word naming several metrics (distance, calories) comes back ambiguous with candidates, and a different measure (RMSSD vs the SDNN that Apple Health stores) is refused with the reason: nothing is guessed. get_health_metrics, get_trends, compare_periods, get_structured_export and correlate_metrics accept the same aliases and report resolvedFrom when they used one; other tools take the export's own names. The export holds one value per metric per day, merged across sources by Apple Health, so this tool states honestly whether per-source disagreement can be seen in the file (exports that record per-source attribution carry src/by and a sources block; others report it as not available) rather than inventing it.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "resolve_metric"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesAny spelling of a metric, e.g. steps, StepCount, Body Weight, VO2 max.
unitNoUnit of value, e.g. lb, mmol/L, degF, km, %. Unknown units are refused, never guessed.
valueNoOptional value to convert into the canonical unit. Pass with unit.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.6.3

TDQS

A4.6/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnly, idempotent), but the description goes well beyond them: percentages are 0-to-1 fractions, unit variants come with exact conversion formulas, ambiguous multi-metric words return candidates, and a different measure (RMSSD vs SDNN) is refused rather than guessed. It also discloses that per-source attribution is only present when exports carry src/by, which is genuine behavioral context.

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?

Purpose and accepted inputs are front-loaded and every sentence carries information, but the closing sentence about source attribution and merged-across-sources semantics is long and somewhat peripheral to the lookup job, making the whole denser than necessary.

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

Completeness5/5

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

There is no output schema, yet the description fully describes what comes back (canonical metric, unit, unit variants with formulas, whether the export holds it) plus conversion, ambiguity and refusal behavior. An agent has everything needed to select and invoke it correctly.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3; the description still adds value by explaining the conversion pairing ('Pass {value, unit} to convert one value, e.g. 180 lb to kg') and the refusal rule for unknown units, beyond what the schema states. It does not add format constraints on `name` that the schema lacks.

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 opening sentence states a precise verb and resource: 'Look a metric name up in the canonical naming and unit table.' It then enumerates accepted input forms and return contents, making it clearly distinguishable from siblings like list_metrics or get_health_metrics without opening either schema.

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

Usage Guidelines4/5

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

It names which siblings accept the same aliases (get_health_metrics, get_trends, compare_periods, get_structured_export, correlate_metrics) and notes that other tools require the export's own names, which tells the agent when resolution is needed. It stops short of an explicit directive ('call this first when the name is ambiguous'), so it is clear context rather than full when/when-not 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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