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get_recent_activities

Get a workout digest for a chosen period: totals per sport and recent runs classified as Quality, Long Run, or Easy. Use this to see actual training before recommending next sessions.

Instructions

Workout digest: totals per sport plus the latest workouts, each run classified Quality / Long Run / Easy (from training effect and duration). Use to see what was actually trained before recommending the next session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
period_daysNoWindow length in days.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden. It signals a read-only digest ('Use to see') and discloses non-obvious classification logic ('Quality / Long Run / Easy, from training effect and duration'), which is genuinely useful. It doesn't address auth or side effects, but none are suggested by the tool.

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?

Two tight sentences: the first packs the output shape and classification rule, the second gives the use case. Every phrase earns its place and there is no redundant or generic filler.

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?

For a one-parameter read tool with an output schema, the description covers the essential return content, the classification behavior, and the intended use context. It could be slightly stronger by tying period_days to 'recent' or noting any limit on how many workouts are returned, but these are minor gaps.

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 coverage is 100%, and the single parameter's meaning ('Window length in days') plus min/default/max is fully documented in the schema. The description adds no extra parameter-level information, so the baseline 3 is appropriate.

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 what the tool returns: 'totals per sport plus the latest workouts' with runs classified into Quality / Long Run / Easy. It stops short of a 5 because it uses a noun-phrase ('Workout digest') rather than an explicit verb, and it doesn't name sibling tools to sharpen differentiation.

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?

'Use to see what was actually trained before recommending the next session' gives a clear, practical when-to-use context. It does not explicitly mention alternatives or when-not-to-use, so it earns a 4 rather than a 5.

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