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DanielTomaro13

sportsdata-mcp

nhl_club_schedule

Read-onlyIdempotent

Retrieve a complete NHL team season schedule with results, including scores, game types, and venues, for any season by supplying team abbreviation and season.

Instructions

One club's entire season schedule with results — the team game log.

Returns: {games:[{id, gameDate, gameType, gameState, homeTeam:{abbrev, score}, awayTeam:{abbrev, score}, gameOutcome:{lastPeriodType}, venue, neutralSite}], currentSeason, previousSeason, nextSeason, clubTimezone} (~200 KB for a full season)

Example: Toronto's full 2024-25 season {"team": "TOR", "season": "20242025"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
teamYes3-letter club abbreviation. Required — part of the URL path.
seasonYesConcatenated-year season, e.g. 20242025. Required — part of the URL path.
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint. The description adds useful context: response size (~200 KB), auth requirements ('Auth: none needed'), and a detailed return shape. It doesn't cover rate limits or data freshness but goes beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: a one-sentence summary, a compact return format snippet, an example, and an auth note. All content is relevant, though the return snippet is somewhat lengthy, it earns its place by showing the response shape.

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?

Given the tool's simplicity and strong annotations, the description covers the key aspects: purpose, response structure, size, example, and auth. No output schema exists, but the return snippet compensates well. It doesn't need further detail for a read-only data retrieval tool.

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 full descriptions for both parameters with 100% coverage. The description's example adds concrete values but no additional semantic meaning beyond the schema, so it meets the baseline without compensating for any gaps.

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 explicitly states 'One club's entire season schedule with results — the team game log,' which clearly defines a specific resource and scope. It distinguishes itself from broader sibling tools like nhl_schedule by focusing on a single club's full season.

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

Usage Guidelines4/5

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

It provides clear context that this is for a single club's full season and includes a concrete example (TOR, 20242025). However, it does not explicitly name alternative tools or state when not to use it, so it lacks explicit exclusions.

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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