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csikosaron98

Intervals.icu MCP Server

by csikosaron98

delete_events_by_date_range

Remove scheduled events from an athlete's Intervals.icu calendar by providing start and end dates, effectively cleaning up unwanted entries in bulk.

Instructions

Delete events for an athlete from Intervals.icu in the specified date range.

Args: athlete_id: The Intervals.icu athlete ID (optional, will use ATHLETE_ID from .env if not provided) api_key: The Intervals.icu API key (optional, will use API_KEY from .env if not provided) start_date: Start date in YYYY-MM-DD format end_date: End date in YYYY-MM-DD format

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
end_dateYes
athlete_idNo
start_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly states that this is a delete operation, but it does not mention whether deletion is permanent/irreversible, whether all events in the range are affected, whether any confirmation is required, or what side effects may occur. For a destructive bulk operation, this is a significant gap.

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?

The description is front-loaded with a clear one-sentence purpose, followed by a compact Args list. Every line provides useful information and there is no fluff, repetition, or irrelevant detail.

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?

An output schema exists, so return-value documentation is not required. However, for a destructive tool with no annotations, the description omits important operational context such as irreversibility, range inclusivity, and potential impact on related data. The parameter documentation is strong, but the behavioral context is incomplete for safe use.

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?

Schema description coverage is 0%, but the description compensates well by documenting all four parameters. It explains that athlete_id and api_key are optional and fall back to .env values, and it specifies the YYYY-MM-DD format for start_date and end_date. It could add date-range boundary semantics (inclusive/exclusive) but otherwise adds substantial meaning beyond the 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 ('Delete'), a resource ('events for an athlete from Intervals.icu'), and a clear scope ('in the specified date range'). This also distinguishes it from the sibling delete_event, which addresses a single event rather than a date-range bulk deletion.

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 usage context is implied by the name and description: use this tool when deleting multiple events by date range. However, it does not explicitly contrast it with alternatives like delete_event or explain when one should be preferred over the other, so guidance is only implicit.

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