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fanduel_research_projection_slates

List FanDuel daily-fantasy slates for a sport to get the slate_id needed by daily projections. Filter by date for MLB, NBA, NHL or by week/season for NFL; golf returns event IDs.

Instructions

FanDuel Research projection slates. Lists the daily-fantasy slates (the contest pools such as Main, All Day or a single game) of a sport, which the DAILY projections need as slate_id. Defaults to today; pass date for MLB, NBA and NHL, or week and season for the NFL, to read another day (past days list their slates too; a day with no games returns an empty list). Golf also returns the current events whose id is the projections' event_id.

Input Schema

NameRequiredDescriptionDefault
dateNoDay as `YYYY-MM-DD`; MLB, NBA and NHL only; cannot be combined with `week` or `season`
weekNoNFL week, 1 to 30; NFL only, usually with `season`
sportYesSport
seasonNoNFL season year such as `2026`; NFL only

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.16

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description usefully discloses behavior beyond the schema: default date handling, sport-specific parameter behavior, past-day support, empty-list behavior when no games exist, and special golf event returns. It does not explicitly state side-effect freedom, permissions, or limits, but the listing behavior is clear.

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 front-loaded and compact for the amount of behavioral detail it conveys. The opening phrase is somewhat redundant with the tool name, but the remaining sentences are dense and purposeful.

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?

For a four-parameter listing tool with no output schema and no annotations, the description covers purpose, usage context, sport-specific parameter behavior, edge cases, and the key return concepts. It does not fully enumerate returned slate fields, but it provides enough context to call the tool 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 parameter documentation is already strong. The description still adds value by explaining the default of today and how `date` versus `week`/`season` is used to read other days for different sports.

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 states a specific verb and resource: it lists daily-fantasy slates for a sport. It also distinguishes the tool from the projections endpoint by explaining that the returned slates provide the `slate_id` that daily projections require.

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 gives clear context for when to use the tool: to obtain slate IDs needed by daily projections, defaulting to today. It explains how to read another day for MLB/NBA/NHL versus NFL, but it does not explicitly name alternative sibling tools or state when not to use this 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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