ncaa_get_scheduleFetch a college team's NCAA schedule for a given sport, team ID, and optional year to view season matchups.
Get a team's NCAA schedule for a season.
| Name | Required | Description | Default |
|---|---|---|---|
| year | No | Year (e.g. 2024) | |
| sport | Yes | Sport name, e.g. "football", "basketball" | |
| fields | No | Keys to keep (comma-separated). | |
| team_id | Yes | NCAA team ID |
Changes observed during successful MCP inspections.
v1.4.1Input schema / $schemaRemoved value: -"http://json-schema.org/draft-07/schema#"Input schema / properties / fieldsAdded value: +{
+ "description": "Keys to keep (comma-separated).",
+ "type": "string"
+}v1.3.0Input schema / additionalPropertiesRemoved value: -falsev1.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and open-world behavior, so the description carries a lower burden. Yet it adds no behavioral context beyond the annotations—such as default season behavior, return format, or pagination—offering zero value beyond structured fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately sized for its content and avoids clutter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four parameters, full schema coverage, and no output schema, the description is minimally adequate. It fails to clarify default season behavior or what the schedule includes (e.g., past vs. future games), which are relevant for an agent's decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters. The description adds no meaning beyond what the schema provides (e.g., it doesn't explain valid formats for 'year' or the purpose of the 'fields' parameter), so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Get') and resource ('a team's NCAA schedule for a season'), clearly distinguishing it from most sibling tools. However, it does not differentiate from closely related tools like ncaa_get_scoreboard or ncaa_get_game, leaving room for confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives (e.g., ncaa_get_scoreboard, ncaa_get_game, or espn_get_team_schedule). There are no exclusions, prerequisites, or context about appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.