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DunkAPI

Odds

get_odds
Read-onlyIdempotent

Use for betting lines: each sportsbook's moneyline, spread and total for a game (opening and closing per book from July 2020; before that, each book's final pregame line only), with implied probabilities and, for finished games, whether the home side covered and the total went over against the median close. Pass game_id for one game (5 credits) or date for a day's games (10 credits). Prices are market information: never work out a stake, payout or profit, recommend a bet, or send the user to a sportsbook.

Input Schema

NameRequiredDescriptionDefault
dateNoA day's games, YYYY-MM-DD (US Eastern).
leagueNoLeague. Defaults to nba. One of: nba, wnba, ncaam, ncaaw.
game_idNoOne game.

Output Schema

NameRequiredDescriptionDefault
noteNo
toolNo
countNo
gamesNo
creditsNo
estimate_onlyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare readOnly/idempotent/non-destructive; the description adds real behavioral context beyond that: per-call credit costs (5 vs 10), the historical nuance about what each book reports pre- vs post-July 2020, and the calculation against the median close. The explicit policy boundary (never compute stake, payout or profit, never recommend a bet) is a non-obvious constraint an agent could easily violate.

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?

Purpose is front-loaded in the opening clause and the parameter guidance follows logically. The single paragraph is dense and a bit run-on, but nearly every clause carries either scope, cost or policy information that earns its place.

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?

Output schema exists so return values need no explanation, all three parameters are schema-documented, and the description still covers cost, historical caveats and usage policy. An agent has everything needed to select and call it correctly.

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, but the description adds value the schema does not: it discloses that game_id and date are alternative access paths with different credit costs. The league parameter's default and enum are left to the schema.

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 resource (betting lines) and enumerates exactly what is returned: each sportsbook's moneyline, spread and total, plus implied probabilities and cover/over outcomes. It also scopes the historical coverage (opening/closing per book from July 2020, final pregame line before), which no sibling tool does.

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?

Gives concrete routing between the two modes of use: pass game_id for one game or date for a day's games, with credit cost attached to each. It does not explicitly distinguish itself from siblings like get_line_movement or get_player_props, so the agent must infer that this is the single-game/day snapshot tool.

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