technogym-mcp

get_session_heart_rate

Get a full heart-rate trace for a workout session, including timestamped samples, HR zones, and summary (duration, avg/min/max HR, calories, MOVEs, METs).

Instructions

Whole-session heart-rate trace (timestamped samples), HR zones, and session summary (duration, avg/min/max HR, calories, MOVEs, METs).

Args: session_id: The session_id from list_workout_sessions. date: The session's ISO date (recommended; otherwise resolved from history). sample_every_seconds: Downsample factor for hr_samples (default 10; 1 = all).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>"
    },
    "name": "get_session_heart_rate"
  }
}

Input Schema

Name	Required	Description	Default
`date`	No
`session_id`	Yes
`sample_every_seconds`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 8, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden and does add value: it explains date fallback resolution and the sample_every_seconds downsample meaning (1 = all). It doesn't mention auth, rate limits, or error behavior, but for a read-oriented 'get' tool these are minor gaps.

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?

The description is front-loaded with the output overview and then uses a compact Args list. Every sentence is purposeful and there is no fluff.

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

Completeness4/5

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

Given that an output schema exists and the input parameters are fully explained, the definition is largely complete. The only notable absence is explicit routing among sibling tools, but the core usage and behavior are covered well.

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

Parameters5/5

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

Schema description coverage is 0%, and the description compensates fully. All three parameters get semantics beyond their schema types/defaults: session_id provenance, date format/recommendation/fallback, and downsample factor behavior including the meaning of 1.

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

Purpose4/5

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

The description clearly states the tool returns a whole-session heart-rate trace, HR zones, and a session summary, naming the specific resource and output fields. It does not explicitly distinguish itself from sibling get_workout_session, so it stops short of a 5.

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

Usage Guidelines3/5

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

It gives clear input guidance by telling the agent to source session_id from list_workout_sessions and to prefer the session's ISO date with fallback behavior. However, it never states when to use this tool versus alternatives like get_workout_session, so usage is only implied.

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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