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DanielTomaro13

sportsdata-mcp

sportsdataio_nfl_scores

Read-onlyIdempotent

Fetch NFL scores for a specific season and week, including team scores, quarter, time remaining, and point spread/over-under.

Instructions

NFL scores for one season and week.

Returns: [{GameKey, SeasonType, Season, Week, Date, AwayTeam, HomeTeam, AwayScore, HomeScore, Quarter, TimeRemaining, PointSpread, OverUnder, StadiumDetails}] — SHAPE FROM VENDOR DOCS. SeasonType 1=pre, 2=regular, 3=post.

NOTE: this shape is from the vendor's documentation and has NOT been verified against a live response (we hold no key for this provider). Treat it as approximate — inspect the actual payload before relying on a field name.

Example: A week's scores {"season": "2023", "week": 1}

Auth: needs your own key in SPORTSDATAIO_MLB_KEY or SPORTSDATAIO_NBA_KEY or SPORTSDATAIO_NFL_KEY or SPORTSDATAIO_NHL_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weekYesWeek number. Required — part of the URL path.
seasonYesSeason with an optional type suffix: 2023, 2023PRE, 2023POST. The BARE year is the regular season. Required — part of the URL path.
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so safety is covered. The description adds valuable behavioral context: the return shape is from vendor docs and unverified, the meaning of SeasonType values, and the need to inspect actual payload. This goes beyond the annotations without contradicting them.

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 well-organized and concise despite including detailed return shape, caveat, example, and auth info. Each section earns its place, and the information is front-loaded with the core purpose.

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?

For a simple two-parameter read-only tool, the description provides everything needed: inputs, output shape, auth, and a caveat about unverified data. It does not explicitly differentiate from alternative NFL score tools, but the overall coverage is strong.

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?

Both parameters are fully described in the schema (100% coverage), but the description adds extra meaning by explaining the season type suffix (e.g., '2023POST') and clarifying that a bare year means regular season. The example also reinforces parameter usage.

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 clear verb ('returns') and resource ('NFL scores for one season and week'), with a specific scope that differentiates it from sibling NFL tools like sportsdataio_nfl_teams. The explicit return shape clarifies the exact data provided.

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 implies when to use this tool (to get scores for a specified season and week) via the example, but it does not explicitly contrast with alternatives or mention when not to use it. No exclusion criteria or alternative tool recommendations are provided.

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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