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search_exercises

Read-onlyIdempotent

Search 873 exercises by name with muscle/equipment/level filters. Rows are lean (name, ext_id, equipment, level, muscles) — enough to pick one; get_exercise returns instructions and media. Paginates: pass next_cursor back as cursor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYes
levelNo
limitNo
cursorNonext_cursor from the previous response. Omit for the first page.
fieldsNoExtra fields, comma-separated, or `all`.
muscleNo
equipmentNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsNo
next_cursorNo
total_matchedNo

TDQS

A4.7/5.0
Behavior5/5

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

Discloses that results are lean, points to get_exercise for instructions/media, and explains pagination mechanics. This adds valuable behavioral context beyond the annotations (readOnly, openWorld, idempotent) that already indicate a safe, read-only operation.

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?

Two sentences with high information density: purpose first, then row content, the pointer to get_exercise, and pagination. No filler words.

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?

Given the output schema, annotations, and pagination, the description covers the key aspects: what rows contain, how to paginate, and how to get full details. The schema handles field descriptions, so nothing essential is missing.

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 description gives meaning to muscle/equipment/level as filters and clarifies cursor for pagination. With schema description coverage at 29%, the description partially compensates, but it doesn't explain valid values for level/muscle/equipment or the exact behavior of q beyond 'by name.'

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?

The description clearly states 'Search 873 exercises by name with muscle/equipment/level filters,' specifying the exact verb, resource, count, and filter categories. This distinguishes it from sibling tools like get_exercise, which returns full details.

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

Usage Guidelines4/5

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

Provides clear context: rows are lean 'enough to pick one; get_exercise returns instructions and media,' explicitly naming the alternative for full details. It also explains pagination with next_cursor/cursor. However, it doesn't explicitly state when not to use it (e.g., if you already have an exercise ID).

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (meals, workouts, routines, body metrics, etc.). A few pairs like get_progress and get_muscle_recovery overlap in data but differ in usage, and the AI tools are separated by input type. Overall, an agent can reliably select the right tool.

Naming Consistency4/5

Tool names predominantly follow a verb_noun snake_case pattern (get_, log_, update_, delete_, search_, list_). The ai_* prefix is consistent but includes noun-like names (ai_meal_plan, ai_photo_macros) that deviate slightly from verb-first convention. Still predictable and readable.

Tool Count3/5

With 36 tools, the server exceeds the typical 'heavy' threshold, but the scope is broad covering meals, workouts, routines, metrics, AI features, and data sync. Each tool serves a distinct capability, so the count is justified though on the higher end.

Completeness4/5

The server provides solid lifecycle coverage for core resources: meals (create/read/update/delete), workouts (log/get/delete, set updates), body metrics (get/log with profile upsert), routines (list/get/instantiate), and exercise lookup (search/resolve/list). Minor gaps exist for updating/deleting cardio and water entries, but they are not critical.

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