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DunkAPI

Team stats

get_team_stats
Read-onlyIdempotent

Use for team efficiency for a season: pace, offensive, defensive and net rating per 100 possessions, the four factors (eFG%, turnover %, offensive rebound %, free throw rate) and three-point rate, from every box score. Costs 5 credits.

Input Schema

NameRequiredDescriptionDefault
teamNoOne team (id or abbreviation).
leagueNoLeague. Defaults to nba. One of: nba, wnba, ncaam, ncaaw.
seasonNoSeason by the year it ends: 2025 = 2024-25 (default: the latest).
season_typeNo

Output Schema

NameRequiredDescriptionDefault
countYes
teamsYes
methodYes
seasonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover safety (read-only, idempotent, non-destructive, closed-world), so the description's added details are what matter: it aggregates 'from every box score' and states the cost of 5 credits. Those are useful behavioral facts beyond the annotations, though it could say more about defaults or output shape.

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 definition is a single front-loaded sentence: purpose first, then the metric list, then cost. Every clause earns its place by clarifying what gets returned or what it costs.

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

Completeness3/5

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

Output schema and annotations cover return shape and safety, and the description adds cost and aggregation context. However, for a 4-parameter tool with only 75% schema coverage, the missing season_type explanation and lack of sibling routing leave gaps an agent could stumble on.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75%, so the schema documents team, league, and season, but season_type has no description. The tool description adds no parameter-level meaning, such as how season_type interacts with season or what values are valid beyond the enum.

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 states a specific verb-and-resource pairing: team efficiency stats for a season, with concrete metrics (pace, ratings, four factors, three-point rate). It is clear what the tool returns, but it does not distinguish itself from potentially overlapping siblings such as get_ratings or get_standings.

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

Usage Guidelines3/5

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

'Use for team efficiency for a season' implies the use case, but there is no explicit guidance on when to choose this over get_ratings, get_standings, or get_player_games. No exclusions or alternatives are named.

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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Directories

Listed in ChatGPT · DunkAPI

Last observed