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Glama

getActivitySets

Retrieve strength-training exercise sets for a Garmin activity from its original .FIT file, including reps, weight, set time, rest, and estimated 1RM for workout analysis.

Instructions

Strength training sets of an activity, read from the original .FIT file. One entry per exercise, in the order first done, with its movement category, its primary and secondary muscles (from Garmin's exercise catalogue) and its active sets: reps, weight (kg, absent when none was recorded), set time in seconds and the rest after the set (restSec). Each exercise with weight also has top (the heaviest set of 1 to 12 reps, then the most reps; without one, the heaviest set) and e1rmKg (the best estimated 1RM, Epley, of its sets of 1 to 12 reps; null when it has none). Exercise names are stable across sessions, so they can be used for per-exercise trends. Edits made later in Garmin Connect (renamed exercises, corrected reps or weights) are not in the .FIT file.

Input Schema

NameRequiredDescriptionDefault
activityIdYesGarmin activity id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does so well: it discloses the data source (.FIT file), the important caveat that later Garmin Connect edits are not reflected, and field-level nullability (weight absent, e1rmKg null). It stops short of stating auth needs or performance characteristics, so not a 5.

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 core return-shape info is front-loaded in the first sentence and the rest unpacks fields. It is dense and slightly run-on across many clauses, but nearly every clause conveys distinct, useful data (top, e1rmKg, restSec), so little is wasted.

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, so the description must explain return values, and it does so thoroughly—per-exercise entries, set fields, derived top/e1rmKg definitions, and the .FIT-edit caveat. An agent has enough to interpret the output correctly.

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

Parameters3/5

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

Only one parameter (activityId) and schema description coverage is 100%, so the schema already documents it. The description adds no additional semantics about activityId beyond what the schema provides, matching the baseline 3 for high-coverage schemas.

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?

States a specific verb and resource: reads strength training sets from an activity's original .FIT file, one entry per exercise. This is clearly distinguishable from siblings like getActivityLaps and getActivityWorkouts, which cover different data.

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

Usage Guidelines3/5

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

Usage is implied by the resource name and 'strength training sets' framing, so an agent can infer this is for strength-workout exercise breakdowns. However, it never explicitly says when to reach for this versus getActivityLaps or getActivityWorkouts, and gives no exclusions or alternatives.

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