matrix-workouts-mcp

summarize_history

Summarize training volume by week or month, including rides, time, distance, work, average power, heart rate, and all-time power curve to identify trends and bests.

Instructions

Training volume per week or month — rides, time, distance, work, average power and heart rate — plus the all-time power curve over the matched rides. This is the tool for questions about trends, totals and bests.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "summarize_history"
  }
}

Input Schema

Name	Required	Description
`to`	No	Inclusive end date, YYYY-MM-DD.
`from`	No	Inclusive start date, YYYY-MM-DD.
`bucket`	No	Default month.
`windowsSeconds`	No	Power-curve durations. Default 10, 30, 60, 300, 600, 1200, 3600.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 14, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are present, so the description carries the behavioral burden. It does disclose aggregation behavior and the output metrics, including the all-time power curve over matched rides. However, it does not state whether the operation is read-only, how 'matched rides' are determined, or what the overall response shape looks like.

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 two sentences with no filler, and the core capability is front-loaded. The long em-dash list makes it slightly dense, but every part earns its place.

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?

Without annotations or an output schema, the description provides a solid summary of outputs but omits operational context such as the meaning of 'matched rides' relative to the date range, default bucket/window behavior, and whether refresh_history is a prerequisite. Parameter details are covered by the schema, but the tool-level context is only partially complete.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all four parameters. The description reinforces the connection to bucket (week/month) and windowsSeconds (power-curve durations), but adds no meaning beyond what the schema already provides.

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 identifies the resource (training history), the aggregation granularity (week/month), and the specific metrics returned (rides, time, distance, work, average power, heart rate, power curve). It lacks an explicit verb like 'summarizes' and does not explicitly contrast with sibling compare_workouts, but the scope is unambiguous.

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 sentence 'This is the tool for questions about trends, totals and bests' gives the agent a clear signal about when to select this tool. It does not mention exclusions or name alternative sibling tools, so it stops short of full routing guidance.

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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