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DanielTomaro13

sportsdata-mcp

nbl_team_stats

Read-onlyIdempotent

Retrieve NBL team statistics for a season, including totals and per-game averages for assists, rebounds, blocks, steals, turnovers, and shooting percentages. Specify the season start year and optional phase to get the data.

Instructions

Team statistics for a season — totals and per-game averages across assists, rebounds (offensive/defensive), blocks, steals, turnovers, and shooting (field goals / three-pointers / free throws made-attempted-percentage).

Returns: {type, count, data:[{team, assists, assists_average, defensive_rebounds, blocks, steals, turnovers, field_goals_made, field_goals_attempted, field_goals_percentage, three_pointers_percentage}]}

Example: Team stats, current season {"year": 2025, "seasonType": "regular"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesSeason START year — 2025 = NBL26 (current 2025-26 season), 2026 = NBL27. Required — part of the URL path.
seasonTypeNoSeason phase (default regular).regular
Behavior4/5

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

Annotations already state readOnlyHint and idempotentHint. The description adds a concrete return shape (type, count, data array with field names) and states no auth is needed. This supplements the annotations without contradicting them.

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 succinct and well-organized: a one-sentence purpose, a return shape snippet, an example request, and an auth note. Every sentence adds value and the structure is easy to scan.

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

Completeness5/5

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

For a simple stats tool with two well-documented parameters, the description covers the essentials: what data is returned, how to invoke it (example), and auth requirements. No external output schema, so the return snippet fills that gap.

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 coverage is 100%, with detailed descriptions for both 'year' and 'seasonType'. The description adds an example but no additional parameter semantics beyond what the schema already provides, so the baseline 3 is appropriate.

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 tool returns team statistics for a season, listing the specific stats categories (totals and per-game averages). It is clear what the tool does, though it does not explicitly differentiate from sibling tools like nbl_player_stats or nbl_stat_leaders.

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?

The description implies when to use it: when you need team-level season totals/averages, with an example request for the current season. It does not explicitly exclude alternatives or state when not to use it, but the context is clear enough for an agent to decide.

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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