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get_wellness

Retrieve wellness metrics like HRV, resting heart rate, sleep quality, and fatigue scores from intervals.icu data to analyze athletic recovery and training readiness.

Instructions

Get wellness data including HRV, resting HR, sleep, and fatigue scores.

Args: oldest: Start date in YYYY-MM-DD format (inclusive). newest: End date in YYYY-MM-DD format (inclusive).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
oldestNo
newestNo

Implementation Reference

  • main.py:84-100 (handler)
    Main handler function for get_wellness tool. Makes API request to /athlete/{ATHLETE_ID}/wellness with optional date filters (oldest, newest) and returns wellness data including HRV, resting HR, sleep, and fatigue scores.
    @mcp.tool()
    def get_wellness(
        oldest: str | None = None,
        newest: str | None = None,
    ) -> list:
        """Get wellness data including HRV, resting HR, sleep, and fatigue scores.
    
        Args:
            oldest: Start date in YYYY-MM-DD format (inclusive).
            newest: End date in YYYY-MM-DD format (inclusive).
        """
        params: dict[str, Any] = {}
        if oldest:
            params["oldest"] = oldest
        if newest:
            params["newest"] = newest
        return _get(f"/athlete/{ATHLETE_ID}/wellness", params)
  • main.py:85-88 (schema)
    Type hints define the input/output schema: two optional string parameters (oldest, newest) and a list return type.
    def get_wellness(
        oldest: str | None = None,
        newest: str | None = None,
    ) -> list:
  • main.py:84-84 (registration)
    FastMCP @mcp.tool() decorator registers the get_wellness function as an MCP tool.
    @mcp.tool()
  • main.py:18-22 (helper)
    Helper function _get makes HTTP GET requests to the Intervals.icu API. Used by get_wellness to fetch wellness data.
    def _get(path: str, params: dict[str, Any] | None = None) -> Any:
        with _client() as client:
            r = client.get(path, params=params)
            r.raise_for_status()
            return r.json()
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses what data categories are returned but omits behavioral details such as whether results are aggregated or daily, pagination behavior, or default behavior when date parameters are null.

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 efficiently structured with a clear purpose statement followed by a structured Args section. No sentences are wasted, though the Args format slightly duplicates schema structure that could have been in the schema itself.

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

Completeness3/5

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

For a 2-parameter retrieval tool with no output schema, the description adequately covers inputs but only superficially covers output structure (listing metrics without indicating if returned as array, daily snapshots, or averages).

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?

Given 0% schema description coverage, the Args section adds crucial value by specifying the YYYY-MM-DD format and inclusivity of the date bounds. It could improve by noting that both parameters are optional/nullable per the schema defaults.

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 clearly states the tool 'Get[s] wellness data' and specifically enumerates the metrics returned (HRV, resting HR, sleep, fatigue scores), distinguishing it from sibling tools like get_activities (workouts) and get_athlete (profile).

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?

While the description implicitly guides usage by defining the specific data domain (wellness metrics vs fitness or activities), it lacks explicit guidance on when to use this versus get_fitness or whether date parameters are required for optimal use.

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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