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nitinchakravarthy

Workout Tracker MCP Server

get_exercises_by_target_muscle

Retrieve exercises for a specific target muscle, with configurable limit and offset to control result size and pagination.

Instructions

Get exercises targeting a specific muscle.

Args:
    target: Target muscle to filter by (e.g., 'biceps', 'triceps', 'quads', 'hamstrings')
    limit: Maximum number of exercises to return (default: 20, max: 100)
    offset: Number of exercises to skip (default: 0)

Returns:
    List of exercises targeting the specified muscle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
offsetNo
targetYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose pagination behavior via limit/offset defaults and the maximum limit, and states the return type. It does not mention ordering, empty-result behavior, exact-match semantics, or invalid target handling, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured with Args and Returns sections. Every sentence adds information, and the core purpose is front-loaded without any filler.

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?

For a simple filtered read tool with three parameters, the description covers the required parameter, optional pagination, and return shape. With an output schema available, deeper return details are unnecessary; it could add only minor context like valid muscle sources or invalid-target behavior.

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

Parameters5/5

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

The schema provides 0% description coverage, but the Args section fully compensates. It gives concrete muscle examples for target, default and maximum for limit, and default for offset, enabling an agent to populate all parameters correctly.

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 opens with a clear verb and resource: 'Get exercises targeting a specific muscle.' The phrase 'specific muscle' distinguishes it from sibling tools like get_exercises_by_body_part and get_exercises_by_equipment, though it does not explicitly name those alternatives.

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 tool name and first sentence: use this when filtering exercises by target muscle. However, there is no explicit guidance about when to prefer this over search_exercises, get_all_exercises, or the body-part/equipment variants.

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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