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Glama

get_training_stats

Totals gym sessions, strength sessions, training minutes, calories, volume and energy between two inclusive dates, answering questions like 'how was my week?'

Instructions

Totals between two dates (YYYY-MM-DD, inclusive): gym sessions, strength sessions, training minutes, calories, volume and energy — for questions like "how was my week?".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYes
startYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
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 burden. It usefully discloses the date format (YYYY-MM-DD) and that both bounds are inclusive, plus the exact metric set returned, but it never explicitly confirms this is a read-only aggregation or how large ranges are handled.

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?

A single front-loaded sentence that begins with the verb and immediately scopes the date range, then lists outputs. Efficient and waste-free, though the metric enumeration is slightly long.

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?

With no annotations and no output schema, the description does the important work of naming the returned aggregate fields (sessions, minutes, calories, volume, energy) and the date semantics. It is nearly complete for a simple two-param aggregation tool; only the read-only nature is left implicit.

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 for both parameters, and it does: it fixes the format as YYYY-MM-DD and clarifies that the interval is inclusive. That resolves the main ambiguity an agent would have about start/end, though it doesn't say which bound drives the window if reversed.

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 (totals) and resource (training metrics) and enumerates the exact outputs, so an agent can distinguish it from detail-oriented siblings like get_session_detail or get_athlete_snapshot. It stops short of naming a sibling it must not be confused with, so it is clear but not fully differentiated.

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?

The phrase "for questions like 'how was my week?'" implies an aggregate-over-a-range use case, which is genuine guidance. However, it never states when to prefer this over overlapping siblings such as get_athlete_snapshot or compare_sessions, so usage is only implied.

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