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jakub-m-arch

Intervals.icu MCP Server

by jakub-m-arch

Add a gear reminder

add_gear_reminder

Set maintenance or replacement reminders for gear by defining limits like distance, days, hours, or activity count. Schedule alerts for when gear needs attention.

Instructions

Add a replacement or maintenance reminder to gear, e.g. "replace shoes after 600 km". Set at least one limit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
nameYese.g. "Replace" or "Chain wax".
hoursNo
gear_idYes
activitiesNo
distance_kmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
gearYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already establish that this is a write operation (readOnlyHint=false) and not destructive. The description adds one useful behavioral rule: at least one limit must be set. Beyond that, it does not explain what happens when multiple limits are supplied or describe side effects, which is acceptable given the existing annotations but not richly transparent.

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 brief sentences communicate the core purpose, give an illustrative example, and state an important constraint. There is no filler and the example is front-loaded, making this easy to parse quickly.

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?

With an output schema present, returning details do not need to be explained, and the annotations cover safety-relevant behavior. The description captures the main operation and the 'at least one limit' rule. However, for a tool with six parameters and weak schema descriptions, the lack of explicit mapping between 'limits' and the actual parameter names leaves meaningful ambiguity.

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

Parameters2/5

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

Schema description coverage is only 17%, so the description carries an unusually high burden for explaining parameters. It introduces the concept of 'limits' and gives the 600 km example, but it never names days, hours, activities, or distance_km as the limit fields, nor does it clarify how multiple limits interact. gear_id and name semantics are left entirely to the schema. Some meaning is added, but not enough to compensate for the sparse 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 states a specific verb ('Add') and resource ('replacement or maintenance reminder to gear'), reinforced with a concrete example like 'replace shoes after 600 km'. It is clearly distinct from the sibling update_gear_reminder because it describes creating a new reminder, not modifying an existing one.

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?

The description makes the intended use case clear (adding a reminder to gear) and adds a usage constraint ('Set at least one limit'). However, it never mentions alternatives like update_gear_reminder or explains when the agent should pick this tool over a related one, so the differentiation is left mostly to the tool name and the agent's inference.

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