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Glama

get_muscle_imbalances

Retrieve EGYM muscle imbalance analysis to identify agonist-antagonist and left-right strength differences, helping you target training and address imbalance risks.

Instructions

EGYM's analysis of muscle imbalances (agonist/antagonist, left/right).

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden, and it discloses almost nothing: no statement that this is a read-only retrieval, no time window or scoping (does it cover the latest assessment or all history?), no permission or prerequisite context. The presence of an output schema relieves it of explaining return values, which keeps this above a 1.

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 short sentence with zero filler, front-loading the resource and immediately qualifying it with the two analysis axes. It is appropriately sized, though it is on the edge of under-specification rather than genuine economy.

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 zero-parameter tool with a published output schema, the description covers what the tool returns at a high level, which is the main thing needed. What is missing is any framing of scope or freshness — an agent cannot tell whether the analysis is current or historical, which matters for how results should be presented alongside siblings like get_strength_history.

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?

The tool takes zero parameters, so there is no parameter semantics for the description to add; the baseline of 4 applies. No parameter meaning is missing or misrepresented.

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?

The description identifies the resource precisely (muscle imbalance analysis) and even names the two axes evaluated: agonist/antagonist and left/right. It is a noun phrase rather than a verb+resource construction, and it does not explicitly contrast itself with neighbours like get_strength_status or get_body_composition, but the subject matter is distinct enough that confusion is unlikely.

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 — nothing says whether this is a current snapshot, a historical view, or how it relates to get_strength_status / get_body_composition. The agent must infer the use case entirely from the tool name.

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