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DanielTomaro13

sportsdata-mcp

cfbd_games

Read-onlyIdempotent

Get college football games for a season with scores, venue, and attendance. Filter by year, team, week, conference, and season type, including postseason.

Instructions

Games for a season with scores, venue and attendance. year is required.

Returns: [{id, season, week, season_type, start_date, neutral_site, conference_game, venue, home_team, home_points, home_line_scores:[…], away_team, away_points, excitement_index, home_post_win_prob}] — SHAPE FROM VENDOR DOCS.

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: 2024 week 1 {"year": 2024, "week": 1}

Auth: needs your own key in CFBD_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamNoOne school's games.
weekNoWeek number.
yearYesSeason year.
conferenceNoConference abbreviation.
seasonTypeNoBowl games need 'postseason' — they are INVISIBLE under the default.regular
Behavior4/5

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

Beyond the annotations (readOnlyHint, idempotentHint, openWorldHint), the description discloses the return shape, notes that it is unverified from vendor docs, and mentions the required API key. This adds meaningful context about expected output and operational constraints.

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?

The description is well-structured with a clear opening, return shape, caveat note, example, and auth requirement. It is slightly longer than necessary due to the example, but all sections serve a purpose and it 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 read-only tool with no output schema, the description provides a return shape, required parameter, auth note, and a critical caveat about unverified data. The schema fills in parameter details, making the overall context adequate for an agent to select and invoke the tool correctly.

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?

The input schema already provides descriptions for all parameters (100% coverage), so the bar is at baseline. The description only adds an example with `year` and `week`, which does not introduce new semantic meaning beyond the schema's existing parameter descriptions.

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 clearly identifies the resource as 'Games for a season with scores, venue and attendance,' which distinguishes it from sibling CFBD tools like cfbd_teams and cfbd_rankings. It lacks an explicit verb like 'list' or 'get,' but the resource and focus are unambiguous.

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 states that `year` is required and provides an example with `week`, implying when to use it for season-specific game data. However, it does not explicitly mention alternatives or when not to use this tool, nor does it reference sibling tools for comparison.

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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