get_sports_scoresReturns current and recent scores for Arizona sports teams — Cardinals (NFL), Suns (NBA), D-backs (MLB), Mercury (WNBA), ASU Sun Devils, Arizona Wildcats, NAU Lumberjacks, and UFC events. Powered by ESPN.
| Name | Required | Description | Default |
|---|---|---|---|
| team | No | Filter by team — omit for all Arizona teams |
| Name | Required | Description | Default |
|---|---|---|---|
| scores | Yes | ||
| updated | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "scores": {
+ "additionalProperties": {},
+ "type": "object"
+ },
+ "updated": {
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "updated",
+ "scores"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds that results are powered by ESPN and cover 'current and recent' scores, which is useful but not extensive. There is no contradiction with annotations.
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 two sentences, front-loading the core functionality and data source. Every word serves a purpose, with no extraneous information. It is highly efficient.
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?
For a simple tool with one optional parameter and an output schema present (per context signals), the description adequately explains what it does and where the data comes from. No additional details are necessary for correct usage.
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?
The single parameter 'team' is fully documented in the schema with an enum and description (100% coverage). The description reinforces the list of teams in prose, but adds no additional semantic detail beyond what the schema provides. Baseline score of 3 is appropriate.
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 explicitly states that the tool returns current and recent scores for specific Arizona sports teams and UFC events, powered by ESPN. It lists teams by name and league, making the purpose very clear and distinguishing it from sibling tools that cover unrelated domains like weather, events, or music.
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?
The description clarifies that the tool is for Arizona sports scores and provides a list of supported teams. While it does not explicitly state when not to use it or alternatives, the scope is narrow enough to infer appropriate usage. The sibling tools are mostly unrelated, so the context is adequate.
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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