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List registration windows

list_registration_windows
Read-onlyIdempotent

Registration windows on record across clubs, for questions like 'which clubs in Ohio have registration open now' or 'what opens in January'. Filter by state, town, club name words, status and dates. Each window has its opening and closing dates, season, source link and verification.

Input Schema

NameRequiredDescriptionDefault
toNoOnly windows overlapping up to this date (YYYY-MM-DD; a range is at most 400 days).
cityNoTown or city name.
dateNoOnly windows that cover this date (YYYY-MM-DD).
fromNoOnly windows overlapping from this date (YYYY-MM-DD).
limitNoHow many results (default 10, at most 25).
queryNoWords of a club's name or town.
stateNoTwo-letter US state code, for example OH or PA.
cursorNonext_cursor from the previous answer, for the next page of the same search.
statusNoopen (covers today) or upcoming (opens later).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety burden is low; the description still adds value by disclosing what each returned window contains (opening/closing dates, season, source link, verification), which is important for judging data trustworthiness. It omits pagination/cursor behavior and the result cap, both of which live only in the schema.

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?

Scope is front-loaded in the first clause, followed by concrete example queries, filter guidance and return contents – no filler sentences. Phrasing is slightly awkward ('on record across clubs') but the content is dense and earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only, nine-param search tool with full schema coverage and no output schema, the description supplies everything an agent needs: the domain, the driving questions, the filter axes, and the shape of returned records. The absence of output schema is offset by the explicit list of per-window fields.

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 all nine parameters including the 400-day range cap and enum values are already documented. The description's 'filter by state, town, club name words, status and dates' merely restates them at a high level without adding syntax or interaction semantics (e.g., how date vs. from/to combine).

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 resource (registration windows across clubs) and anchors it with sample questions, so an agent immediately knows this is a curated registry of registration periods rather than general club search. It does not explicitly name a sibling like search_clubs to route against, which keeps it below a 5.

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 example questions ('which clubs in Ohio have registration open now', 'what opens in January') effectively demonstrate the intended query shape, and the filter list tells the agent how to narrow. There are no explicit when-not conditions or named alternatives, so it is clear context without exclusions.

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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