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dylangroos

NHL MCP Server

by dylangroos

get-season-stat-leaders

Retrieve NHL skater statistics leaders for specific seasons and game types, including goals, assists, and points rankings.

Instructions

Get NHL skater stats leaders for a specific season and game type

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesStat category (e.g. goals, assists, points)
seasonYesSeason in YYYYYYYY format (e.g. 20232024)
gameTypeNoGame type (2 for regular season, 3 for playoffs)
limitNoNumber of players to return (default: 5)
Behavior2/5

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 states the tool retrieves data ('Get'), implying a read-only operation, but doesn't cover aspects like rate limits, authentication needs, error conditions, or the format/structure of returned data. This leaves significant gaps for a tool with 4 parameters.

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, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes essential information about what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks behavioral context (e.g., data format, limitations), usage guidance relative to siblings, and details about return values. The schema covers parameters well, but the overall context for an AI agent is insufficient.

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?

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain valid values for 'category' or 'season' beyond the schema's examples). Baseline 3 is appropriate when the schema does the heavy lifting.

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 states the action ('Get') and resource ('NHL skater stats leaders'), specifying the scope ('for a specific season and game type'). It distinguishes from some siblings like 'get-current-stat-leaders' by focusing on historical seasons, but doesn't explicitly differentiate from 'get-skater-leaders' which might have similar functionality.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, compare with sibling tools like 'get-current-stat-leaders' for current data or 'get-season-goalie-leaders' for goalies, or specify scenarios where this tool is preferred.

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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