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Glama

get_exercise_data

Retrieve workout logs by client, date range, and activity type to analyze exercise duration, calories, heart-rate zones, and RPE.

Instructions

Workout logs — type, duration, calories, heart-rate zones, RPE.

Args: client_id: Client identifier. start_date: ISO date, inclusive. end_date: ISO date, inclusive. activity_type: Optional filter (e.g. "run", "strength").

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
client_idYes
start_dateNo
activity_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose the returned data shape (type, duration, calories, HR zones, RPE), which is genuinely useful, but says nothing about read-only semantics, authentication/permission requirements, pagination, or what happens when start_date/end_date are omitted (both default to null).

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?

Front-loaded with the resource and its payload, followed by a compact Args block; nearly every line earns its place. Minor redundancy in restating field names already implied by the parameter list.

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?

An output schema exists, so return values need not be explained, yet the description's parameter coverage is its main contribution and it omits which non-required params have null defaults and how a missing date range behaves. Adequate but with a visible gap for a 4-parameter, zero-coverage 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 0%, so the description must compensate, and it largely does: it documents all four parameters inline, marks activity_type as optional with concrete examples ('run', 'strength'), and specifies that start_date/end_date are ISO dates and inclusive.

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?

Names a specific resource (workout logs) and enumerates the concrete fields returned — type, duration, calories, heart-rate zones, RPE — so an agent knows what data lands in the response. It does not, however, differentiate itself from plausible siblings such as get_cardio_metrics or get_fitness_assessment, which may surface overlapping metrics.

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 at all: no statement of when to call this instead of get_cardio_metrics or get_fitness_assessment, no prerequisites, and no exclusions. The activity_type filter is described as 'Optional filter' but the description never explains the scenario that calls for it.

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