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garminconnect-js

garminconnect-js

by DynamicsNinja
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

create_gear

Add shoes, bikes, or other gear to Garmin Connect with first use date, activity types, and distance or duration usage limits in km and minutes.

Instructions

Creates a piece of gear (shoes, bike and so on). Usage limits are given in km and minutes. POSTs /gear-service/gear/v2; defaults usageType="DISTANCE", notes=""; gearType/usageType upper-cased via validateSportKey; converts maxUsageDistanceKm -> maxUsageDistanceMeters (round(km*1000), floor 1) and maxUsageDurationMin -> maxUsageDurationSeconds (round(min*60), floor 1), the opposite direction from addWeighIn's "send raw" rule; returns the response unchecked.

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": {
      "gearType": "<gearType>",
      "brand": "<brand>",
      "model": "<model>",
      "name": "<name>",
      "firstUseDate": "<firstUseDate>"
    },
    "name": "create_gear"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
brandYes
modelYes
notesNo
gearTypeYes
usageTypeNo
firstUseDateYesCalendar date, YYYY-MM-DD (UTC)
activityTypeKeysNo
maxUsageDistanceKmNo
maxUsageDurationMinNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already mark this as a non-read-only, non-destructive, open-world write. The description adds substantial beyond-schema behavior: the POST endpoint, server-applied defaults (usageType=DISTANCE, notes=""), upper-casing of gearType/usageType, unit conversion with rounding and a floor of 1, and that the response is returned unchecked. It omits auth/rate-limit details, but the disclosure is well above the annotation baseline.

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?

Dense but front-loaded: the core purpose leads, followed by endpoint, defaults, and conversion rules in a compact sequence. The comparison to addWeighIn's 'send raw' rule is arguably tangential but does reinforce the direction of the conversion, so little is truly wasted.

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

Completeness3/5

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

For a 10-parameter mutation tool with no output schema and 10% schema coverage, the description covers the non-obvious parameters and normalization but leaves five required/optional fields unexplained and only vaguely states the return behavior ('returns the response unchecked'). It is workable but not complete enough to call the tool confidently without reading the schema.

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 only 10%, so the description must carry the load and it does for the tricky fields: defaults for usageType and notes, case normalization for gearType/usageType, and the km->meters / minutes->seconds conversion with rounding rules. It still says nothing about the meaning of brand, model, name, or activityTypeKeys, so it compensates only partially.

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

Purpose4/5

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

States a specific verb and resource ('Creates a piece of gear') and gives concrete examples (shoes, bike), so an agent knows exactly what entity is produced. It does not explicitly differentiate from nearby siblings like add_gear_to_activity or set_gear_activity_defaults, but create-vs-assign is inferable from the verb.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no mention of prerequisites, and no routing to alternatives such as add_gear_to_activity for attaching gear to a workout. The only contextual hints (units in km/minutes) describe the payload rather than when to call the tool.

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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