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DanielTomaro13

sportsdata-mcp

ncaa_scoreboard

Read-onlyIdempotent

Retrieve current college sports scoreboards for any NCAA sport and division, displaying game scores, status, and contest clock.

Instructions

Current scoreboard for one college sport and division — games with scores, state and clock.

Returns: {updated_at, games:[{game:{gameID, startDate, startTime, gameState, currentPeriod, contestClock, home:{names:{short, full}, score, winner, conferences}, away:{…}, url, network}}]} — note each entry is a one-key object wrapping game

Example: FBS football scoreboard {"sport": "football", "division": "fbs"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNoHyphenated, gendered sport slug: football, basketball-men, basketball-women, ice-hockey-men, lacrosse-men, …football
divisionNofbs/fcs for football; d1/d2/d3 for other sports.fbs
Behavior4/5

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

Annotations already declare readOnly/OpenWorld/idempotent; the description adds a detailed return structure, the note about one-key object wrapping, and Auth:none needed. No contradictions. It doesn't mention rate limits or empty results, but for a read-only scoreboard the critical context is covered.

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 tightly organized: a one-line summary, a Returns block, a structural note, a concrete example, and Auth. Every line carries useful information.

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?

With 100% schema coverage and readOnly/OpenWorld/idempotent annotations, the description needs mainly to explain the return payload; it does so with a detailed pseudo-schema and the one-key quirk. The example further clarifies parameter usage.

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 the baseline is 3; the description's example reiterates the schema defaults (football/fbs) without adding new parameter meaning. No additional semantics needed.

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 opens with 'Current scoreboard for one college sport and division', clearly identifying the tool's resource and scope. It distinguishes from siblings like espn_scoreboard by limiting to one college sport/division, but doesn't name an alternative explicitly.

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?

It establishes clear context: use when you need current NCAA scores for a specific sport/division, with an explicit FBS football example. However, it doesn't state when-not-to-use or name alternatives, so not a 5.

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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