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MoveMate: Gym Workout Tracker

Search exercises

search_exercises
Read-only

Searches MoveMate's exercise library (including the user's own custom exercises). The model must only compose workouts from exercises returned here — never invented ones. Each result carries an exercise_type saying how that movement is measured (reps, time, distance) — it decides which target fields create_planned_workout will accept for it, so read it before writing sets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many exercises to return. Default 20, max 50.
queryNoExercise name or part of it, fuzzy-matched — e.g. "bench press" or "romanian". Omit to browse by muscle_group or equipment.
equipmentNoEquipment name, e.g. "dumbbell", "barbell", "kettlebell" or "bodyweight". Common synonyms are accepted.
muscle_groupNoMuscle group name. Broad lower-body aliases are supported: legs, leg, lower body, and lower-body include quads, hamstrings, glutes, and calves.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeYes
exercisesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuine value beyond them: it discloses that results include custom exercises and that each result carries an exercise_type governing which target fields are valid downstream. It does not mention pagination or ranking behavior, keeping it short of 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.

Conciseness5/5

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

Three sentences, all front-loaded and purposeful: scope first, then the hard constraint, then the downstream dependency. No filler or restatement of the name.

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?

An output schema exists, so return values need not be explained in full, yet the description still highlights the one return field (exercise_type) that gates correct downstream usage. Combined with full schema coverage and read-only annotations, an agent has everything needed to call it 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?

Schema description coverage is 100%, so the schema already documents query, equipment, muscle_group, and limit with examples and aliases. The description adds no further parameter detail, so the baseline 3 applies.

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 (Searches) and resource (MoveMate's exercise library) and clarifies scope by including the user's own custom exercises. An agent can immediately distinguish this from create_custom_exercise or get_exercise_progression.

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

Usage Guidelines5/5

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

Explicitly states the constraint that workouts must only be composed from exercises returned here and never invented, and instructs the agent to read exercise_type before writing sets — directly tying its use to the downstream create_planned_workout call. This is clear when-to-use and when-not-to-invent guidance.

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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