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turnnoblindeye

Wellness Project MCP

list_exercises

Read-onlyIdempotent

Retrieve canonical exercise names grouped by muscle group to match user-described exercises before logging or updating workouts, ensuring proper tracking and NSI score calculation.

Instructions

Returns all canonical exercise names from the exercise library, grouped by muscle group. Call this before log_workout or update_workout to match user-described exercise names to canonical ones. Canonical names ensure proper exercise tracking and NSI score calculation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesHuman-readable result text returned by the tool.

Schema Changelog

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

  1. First observedv1.2.1

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful context by revealing the grouping behavior and explaining that canonical names support exercise tracking and NSI score calculation, which goes beyond the annotations.

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 concise sentences with no filler: output definition, when to call it, and why it matters. The most actionable guidance is front-loaded, and every sentence earns its place.

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?

For a zero-parameter read-only listing tool with an output schema present, the description is complete. It explains the return content, the grouping, the practical invocation timing, and the downstream benefit, leaving no obvious gap for an agent to call it correctly.

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 has zero parameters, so there is no parameter semantics burden on the description. The baseline is 4, and the description appropriately focuses on the return value and usage context rather than inventing parameter details.

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 states a specific verb ('Returns'), a precise resource ('all canonical exercise names from the exercise library'), and an organizing detail ('grouped by muscle group'). It clearly distinguishes this tool from sibling list_* tools by focusing on the canonical exercise library rather than logs, meals, or metrics.

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?

The description explicitly says to call this before log_workout or update_workout to match user-described exercise names to canonical ones. This provides clear contextual guidance, though it does not explicitly discuss when not to use it or name alternatives as exclusions.

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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