Get MLB standings for American and National leagues, grouped by division. Select regular season, wild card, or spring training for any season.
Get MLB standings. Returns American League and National League standings grouped by division. The type enum accepts regularSeason, wildCard, and springTraining.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Standings type | |
| season | No | Four-digit season; defaults to current year |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the transparency burden. It discloses the return grouping and the accepted type enum values, which is helpful. However, it doesn't detail response format, error handling, or edge cases like invalid season values. This is acceptable for a simple read tool but not richly transparent.
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 long, front-loaded with the purpose, and contains no filler. Every sentence adds value: the first states the function, the second details the return grouping and type options.
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?
The tool is simple with only two optional parameters and no output schema. The description explains the core output (standings grouped by division) and type options, which is sufficient for an agent to select and invoke it. It could mention whether standings include win-loss records, but this is not critical for basic use.
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 coverage is 100% for both parameters, but the description adds the enum values for the 'type' parameter, which is crucial for correct invocation. This goes beyond the schema's generic 'Standings type' and earns a score above the baseline.
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 clearly states the tool's function with a specific verb and resource: 'Get MLB standings.' It also specifies the return structure (AL and NL standings grouped by division), distinguishing it from sibling tools like espn_standings or sofascore_standings by its MLB-specific scope and grouping detail.
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 implies usage: when you need MLB standings. It provides clear context about what the tool returns but does not explicitly mention alternatives or when not to use it. This aligns with 'clear context, no exclusions,' so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.