Get training max (1RM estimate) values for exercises. Returns all training maxes, or filter by exercise name.
Args: exercise_name: Optional exercise display name to filter (e.g. 'Barbell Back Squat').
| Name | Required | Description | Default |
|---|---|---|---|
| exercise_name | No | Optional exercise display name to filter (e.g. 'Barbell Back Squat') |
| Name | Required | Description | Default |
|---|---|---|---|
| training_maxes | Yes |
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, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds that invoking with no filter returns all training maxes and with exercise_name returns a subset, plus clarifying that values are 1RM estimates. No side effects or edge cases are disclosed, but this is acceptable for a simple getter.
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?
Three short sentences front-load the core behavior and then cover the optional parameter. No filler, no redundant background, and the structure flows naturally from purpose to filtering behavior.
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 single-optional-parameter read tool with an output schema and readOnly/idempotent annotations, the description is complete. It states both invocation modes (all vs filtered) and clarifies the data meaning (1RM estimate). Nothing needed to call it correctly is missing.
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?
Schema description coverage is 100%; the schema already fully documents exercise_name as an optional display-name filter. The description repeats that same example ('Barbell Back Squat') without adding additional meaning, so it meets the baseline but adds little beyond the schema.
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 opens with a specific verb and resource: 'Get training max (1RM estimate) values for exercises.' It also states the two modes (all values or filtered by exercise name), clearly distinguishing this read tool from the sibling set_training_max and other get_* tools.
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 clearly establishes retrieval context: use it to read training maxes, with an optional filter. It does not explicitly name alternatives such as set_training_max or spell out when not to use the tool, but the read-vs-write contrast is obvious from the sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
