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fanduel_sportsbook_live_count

Returns the number of FanDuel Sportsbook events currently in play for a given market, letting you monitor live activity by state or Ontario (default NJ).

Instructions

FanDuel Sportsbook live event count. Returns the number of events in play in a market, the figure the Sportsbook's homepage shows beside its Live link. It differs by market (for example about 130 in NJ, 107 in PA, 36 in NY and 185 in Ontario on one afternoon) and moves as games start and end, which makes it a cheap way to watch activity. Use the live route to list the events.

Input Schema

NameRequiredDescriptionDefault
stateNoMarket code, including `on` for Ontario; default `nj`

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.16

TDQS

A4.1/5.0
Behavior4/5

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

No annotations are supplied, so the description carries the full burden, and it does well: it discloses that the return value is a single number tied to the homepage Live link, that it differs by market with concrete examples, and that it fluctuates as games start and end. It omits any note on freshness/caching or auth, keeping it from a 5.

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?

Front-loads the core purpose in the first sentence, then adds context and the sibling pointer. The market-count examples are illustrative and slightly verbose but each sentence still carries meaning; nothing is wasted outright.

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 single-optional-param count tool with no output schema, the description is complete enough: what it returns, how it varies, and where to go for the actual event list. Only freshness/auth behavior is left unstated.

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% and the `state` parameter (default `nj`) is already fully documented, so the schema does the heavy lifting. The description reinforces the market concept with value examples (NJ, PA, NY, Ontario) but adds no format or aliasing detail beyond what the schema provides – baseline 3.

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: 'Returns the number of events in play in a market.' It also distinguishes itself from the sibling `live` route that lists the events themselves, so an agent can tell the two apart without opening either schema.

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 frames the tool as a 'cheap way to watch activity' and explicitly points to the `live` route for listing events, which gives clear when-to-use routing. It stops short of stating exclusions (e.g. when a raw count is insufficient), so it falls just shy of a 5.

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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