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set_training_max

Idempotent

Set the training max for an exercise (creates it, or updates an existing one). The training max is the estimated one rep max that workouts compute weights from when an exercise uses percentage of training max.

Args: exercise_name: Exact exercise display name from search_exercises. training_max: The training max value, in the user's units (lb or kg per their settings).

Updating an existing training max recalculates the weight of every workout where the exercise uses percentage of training max. Confirm with the user before changing an existing one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
training_maxYesTraining max in the user's units (lb or kg per their settings)
exercise_nameYesExact exercise display name from search_exercises

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitsYes
outcomeYes
previousNo
training_maxYes
exercise_display_nameYes

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations, the description discloses the upsert behavior (creates or updates), the significant side-effect that updating recalcs every affected workout's weights, and the need to confirm with the user before changing an existing value. This is rich behavioral context that annotations alone do not provide, and it does not contradict them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-structured and front-loaded with the core purpose. The Args section is somewhat redundant with the schema's parameter descriptions, but the rest of the content—definition, side effects, and confirmation rule—earns its place without unnecessary fluff.

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 two-parameter write operation, the description covers purpose, creation/update behavior, side effects, units, and the user-confirmation requirement. It also tells the agent how to source exercise_name. Since an output schema exists, the lack of a return-value description is not a gap.

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?

Schema coverage is 100%, so both parameters are already documented. The description adds value by explaining the conceptual meaning of 'training max' as an estimated one-rep max and its role in percentage-based workout calculations, which goes beyond the schema's bare parameter descriptions.

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 opens with a specific verb ('Set') and a clear resource ('the training max for an exercise'), then clarifies that it creates or updates an existing entry. It also defines what a training max is, so the agent understands exactly what this tool does and how it relates to workouts.

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 makes the context obvious: use this when the user wants to set or update a training max, and it notes that exercise_name must come from search_exercises. It also gives an important usage rule to confirm with the user before overwriting an existing value. It does not explicitly mention alternatives, but no sibling tool provides this same function.

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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