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VSidhArt

Intervals.icu MCP Server

by VSidhArt

get_grouped_activities

Fetch and group fitness activities by sport, day, week, or month to analyze training patterns and create summarized reports from Intervals.icu data.

Instructions

Tool for fetching and grouping activities to reduce data volume and show patterns.

Best for: Analyzing training patterns, summarizing activity by sport/time period, creating training reports, reducing data volume for large date ranges. Not recommended for: Getting individual activity details; real-time tracking. Common mistakes: Using invalid group_by value; requesting details for large datasets. Prompt Example: "Group my activities by sport from January" or "Show me weekly activity summary for last month" Usage Example:

{
  "name": "get_grouped_activities",
  "arguments": {
    "oldest_date": "2024-01-01",
    "newest_date": "2024-01-31",
    "group_by": "week",
    "include_details": false
  }
}

Tool Relationships: Use after get_activities to analyze patterns, or directly for summarized data when individual activities aren't needed. Returns: Grouped activity data with summaries (count, duration, distance) per group.

Parameters

oldest_date : str The oldest date to fetch activities from (format: YYYY-MM-DD). This parameter is required. newest_date : str, optional The newest date to fetch activities from (format: YYYY-MM-DD). If not provided, no upper date limit is applied. group_by : str, optional How to group activities. Options: "sport", "day", "week", "month". Default: "sport" include_details : bool, optional Whether to include filtered activity details in each group. Default: False

Returns

dict Dictionary containing: - groups: Dictionary of groups with summaries - total_activities: Total number of activities - Additional metadata based on grouping type

Raises

ValidationError: If parameters are invalid. IntervalsError: If the API request fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
oldest_dateYes
newest_dateNo
group_byNosport
include_detailsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's purpose, common mistakes (e.g., invalid group_by values), and return structure, though it lacks details on rate limits, authentication needs, or error handling beyond the 'Raises' section. It adds significant value beyond the input schema without contradicting any annotations.

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 with clear sections (Best for, Not recommended, Parameters, Returns, etc.), but it includes redundant elements like the JSON usage example and prompt examples that could be condensed. Most sentences earn their place by providing useful information, though some formatting adds bulk without proportional value.

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 tool with 4 parameters, 0% schema coverage, no annotations, but an output schema, the description is highly complete. It covers purpose, usage guidelines, parameters, returns, errors, and relationships with sibling tools, providing all necessary context for an agent to understand and invoke the tool correctly without relying on structured fields.

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?

Given 0% schema description coverage, the description compensates fully by detailing all parameters in the 'Parameters' section, including their purposes, formats, defaults, and optionality. It explains 'oldest_date' as the oldest date to fetch from, 'newest_date' as an optional upper limit, 'group_by' options, and 'include_details' effect, adding crucial meaning beyond the bare schema.

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 'fetches and groups activities to reduce data volume and show patterns,' which is a specific verb+resource combination. It distinguishes from sibling tools like 'get_activities' by emphasizing grouping and summarization rather than individual activity retrieval, making the purpose unambiguous and differentiated.

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

Usage Guidelines5/5

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

The description provides explicit guidance with 'Best for' and 'Not recommended for' sections, clearly outlining when to use this tool versus alternatives. It mentions using it after 'get_activities' for analysis or directly for summarized data, and warns against using it for individual details or real-time tracking, offering comprehensive usage context.

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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