Get the user's workout settings: unit preference (lbs/kg), weight rounding, and other preferences. Call this early in a conversation so you have context for all subsequent responses.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| units | Yes | ||
| weight_rounding | No | ||
| skip_last_rest_step | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds only timing advice, not additional behavioral traits such as authentication needs, rate limits, or what entities are affected. Since it doesn't contradict annotations, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence front-loads the operation and examples; the second gives actionable usage guidance. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only, zero-parameter getter with an output schema present, the description is sufficient: it defines purpose and provides invocation timing. It doesn't explicitly contrast with sibling tools, but the uniqueness of 'user settings' is clear enough that this omission is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so schema coverage is trivially 100% and the description cannot add parameter-level meaning. The description does clarify the type of data returned (workout settings such as units and rounding), which is relevant to context even though it's not parameter-related. Baseline 4 applies for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('user's workout settings') and gives concrete examples (unit preference, weight rounding), making the tool's role unmistakable. It reads as distinct from the various sibling get_* tools by focusing on global user preferences rather than domain-specific entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to call this tool early in a conversation to have context for subsequent responses, which is clear when-to-use guidance. However, it does not name alternatives or provide any exclusions (e.g., 'use get_coach_profile for coach-specific settings'), so it falls short of a perfect 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
