Skip to main content
Glama

get_workout_input_schema

Retrieve the input schema for constructing valid Garmin workout payloads, ensuring correct structure for strength training.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Tool handler that returns the JSON schema of the WorkoutInput Pydantic model via model_json_schema(). This allows clients to discover the expected input shape for creating workouts.
    @mcp.tool
    def get_workout_input_schema() -> dict:
        return {"schema": WorkoutInput.model_json_schema()}
  • Pydantic model WorkoutInput that defines the schema returned by get_workout_input_schema(). Contains name, type, description, and a list of StepInput steps.
    class WorkoutInput(BaseModel):
        model_config = ConfigDict(extra="forbid")
    
        name: str = Field(min_length=1)
        type: str
        description: str | None = None
        steps: list[StepInput] = Field(min_length=1)
  • The @mcp.tool decorator registers get_workout_input_schema as a tool with the FastMCP server.
    @mcp.tool
    def get_workout_input_schema() -> dict:
  • Calls WorkoutInput.model_json_schema() which is a Pydantic helper method that generates a JSON Schema (draft-07) from the WorkoutInput model definition.
    return {"schema": WorkoutInput.model_json_schema()}
  • StepInput model used by WorkoutInput.steps – defines the shape of each workout step (executable step or repeat group).
    class StepInput(BaseModel):
        model_config = ConfigDict(extra="allow")
    
        stepName: str | None = None
        stepDescription: str | None = None
        stepType: str | None = None
        endConditionType: str | None = None
        stepDuration: float | None = None
        stepDistance: float | None = None
        distanceUnit: str | None = None
        stepReps: float | None = None
        numberOfIterations: int | None = None
        steps: list["StepInput"] | None = None
        target: TargetInput | None = None
        exercise: str | ExerciseInput | None = None
        category: str | None = None
        exerciseName: str | None = None
        weightValue: float | None = None
        weightUnit: str | None = None
Behavior1/5

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

Tool has no description.

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

Conciseness1/5

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

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose1/5

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

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

Usage Guidelines1/5

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

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pranciskus/garmin-workouts-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server