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DunkAPI

List teams

list_teams
Read-onlyIdempotent

Use to find team ids and abbreviations for a season (default: the latest). Every other tool takes a team as an id or abbreviation. Pass league for the WNBA (wnba) or college (ncaam, ncaaw); default NBA. Costs 1 credit.

Input Schema

NameRequiredDescriptionDefault
leagueNoLeague. Defaults to nba. One of: nba, wnba, ncaam, ncaaw.
seasonNoSeason by the year it ends: 2025 = 2024-25. WNBA: the calendar year.

Output Schema

NameRequiredDescriptionDefault
countYes
teamsYes
seasonYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds genuinely new behavioral context not in any structured field: the cost ('Costs 1 credit') and the default season ('the latest'), both of which affect how an agent budgets and interprets a call. It stops short of describing result shape, but an output schema exists to carry that.

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?

Three short sentences, each carrying a distinct payload: purpose, prerequisite routing, league branching, and cost. The purpose is front-loaded and there is no filler or restatement of the title.

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?

With only two optional parameters, full schema coverage, and an output schema handling return values, the description covers everything an agent needs: why to call it, how to select league, what season defaults to, and what it costs.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3; the description earns above that by adding the season default ('the latest'), which the schema does not state, and by mapping the league enum values to real-world meaning (WNBA vs college vs NBA default) rather than just repeating the enum list.

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?

States a specific verb and resource ('find team ids and abbreviations') plus the scoping dimension ('for a season'). The sentence 'Every other tool takes a team as an id or abbreviation' positions it unambiguously against all 17 siblings as the prerequisite lookup tool.

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

Usage Guidelines5/5

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

Tells the agent exactly when to reach for it (before any team-scoped tool, since all others need an id or abbreviation) and how to branch by league: wnba, ncaam, ncaaw, with nba as default. No alternative tool competes for this job, so no exclusion clause is needed.

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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