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lacausecrypto

Sports Hub MCP Server

espn_get_seasons

Retrieve available seasons for any sport and league, including season types (preseason, regular, postseason) and their date ranges.

Instructions

Get available seasons for a sport/league, including season types (preseason, regular, postseason) and date ranges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportYesSport code, e.g. "football", "basketball", "baseball", "hockey", "soccer", "mma", "golf", "tennis", "racing"
leagueYesLeague code, e.g. "nfl", "nba", "mlb", "nhl", "wnba", "college-football", "mens-college-basketball", "eng.1", "usa.1", "ufc", "pga", "atp", "f1"
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys that the tool retrieves seasons with types and date ranges, implying a read-only, non-destructive operation. However, it does not mention any constraints, such as data freshness, required permissions, or what constitutes 'available seasons', leaving minor gaps.

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 a single, well-structured sentence that front-loads the core purpose and includes key specifics. Every word contributes, and there is no redundancy or verbosity.

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?

Although there is no output schema, the description gives a reasonable idea of the return content (season types and date ranges). For a straightforward list retrieval tool, this is sufficient context to set expectations, though a more detailed example would improve completeness.

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 100% coverage for both parameters with clear descriptions. The description mentions 'sport/league' but adds no new semantic information beyond what the schema states. Thus, the description adds no extra value for parameter understanding.

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 clearly states the action ('Get'), the resource ('available seasons'), and the specific information included ('season types and date ranges'), making the purpose immediately understandable. While it doesn't explicitly differentiate from sibling 'get_seasons' tools, the tool name includes 'espn', and the description focuses on sport/league parameters, which associates it with ESPN sports.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives like 'f1_get_seasons' or 'sportsdb_get_seasons'. No conditions, prerequisites, or exclusion criteria are mentioned. The description only states what the tool does, not when it should be chosen.

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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