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Search races

search_races
Read-onlyIdempotent

Find races for a runner: marathons, half marathons and ultras worldwide by name, city, region, country, distance, date window or Boston-qualifier status ("a flat spring marathon in Ohio", "halves near Denver in October"). Returns up to 10 races (20 with an API key) with the next race date, registration status and Marathon Scout guide URL. With no text query, results are in date order.

Input Schema

NameRequiredDescriptionDefault
toNoLatest next race date, YYYY-MM-DD.
fromNoEarliest next race date, YYYY-MM-DD.
limitNo
queryNoRace name or place, e.g. "chicago" or "big sur".
regionNoState or region name as written locally, e.g. Ohio or Bavaria.
countryNoISO 3166-1 alpha-2 code or English name, e.g. US or Japan.
distanceNo
boston_qualifierNotrue for Boston qualifying courses only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limit / maximum
      Previous value: -25New value: +20
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), and the description adds real context beyond them: a result cap of 10 (20 with an API key), the fields returned (next race date, registration status, Marathon Scout guide URL), and date ordering when the query is empty. It does not explain pagination past the cap, empty-result behavior, or error handling.

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?

Three tight sentences with the purpose front-loaded, then capability, then return shape and the no-query ordering rule. Dense but every clause carries information; the parenthetical examples are long but functional.

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?

With no output schema, the description steps in to describe returned fields and the result cap, which is the main thing an agent needs. Remaining gaps (limit default when unspecified, behavior with zero matches, whether region requires country) are minor for a read-only, zero-required-parameter search.

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 coverage is 75%, and the description adds meaning the schema does not: it frames the free-text query as able to carry compound constraints ("a flat spring marathon in Ohio"), and enumerates the filter axes (name, city, region, country, distance, date window, Boston qualifier) so the agent can map intent to separate parameters rather than dumping everything into query.

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?

States a specific verb and resource ("Find races for a runner") plus the exact scope: marathons, half marathons and ultras worldwide, searchable by name, city, region, country, distance, date window or Boston-qualifier status. It is unmistakably a search tool, but never mentions the sibling get_race, so the boundary between searching and fetching a single race is left to inference.

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 quoted natural-language examples ("a flat spring marathon in Ohio", "halves near Denver in October") implicitly show how to shape a query, and the note that no text query yields date-ordered results gives a usable default. However there is no explicit when-to-use/when-not guidance and no pointer to get_race for detail lookups.

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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