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JavaScript
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fanduel_sportsbook_autocomplete

Get FanDuel Sportsbook search suggestions for players, teams, and competitions as a user types a prefix, returning plain and highlighted match text for each result.

Instructions

FanDuel Sportsbook search suggestions. Returns the suggestions the Sportsbook's search box offers while a user types: players, teams and competitions that match the prefix. Each suggestion has its plain text and a highlighted form that wraps the matched characters in <em> tags. Use search/tabs for the full results of a chosen suggestion.

Input Schema

NameRequiredDescriptionDefault
qYesPrefix to complete, 2 to 100 characters, without `<` or `>`
limitNoSuggestions to return, 1 to 50; default 5

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.16

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the load and does so well: it discloses the return shape (a list of suggestions, each with plain `text` and a `<em>`-tagged `highlighted` form) and the matching semantics (prefix match over players, teams, competitions). It omits rate limits, ordering, and empty-result behavior, which are minor for a suggest endpoint.

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 tight sentences with the purpose front-loaded, the return detail second, and the routing hint last. Nothing is redundant with the schema or wasted.

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?

There is no output schema, so the description's explanation of the `text`/`highlighted` pair is what lets an agent consume results correctly, and it delivers that. Only ordering, deduplication, and empty-prefix behavior are left unexplained.

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%, so both `q` (2-100 chars, no `<`/`>`) and `limit` are already documented. The description's 'match the prefix' adds only a slight conceptual tie to `q` and says nothing extra about `limit`. Baseline 3 is appropriate.

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 ('FanDuel Sportsbook search suggestions') and immediately narrows scope: 'suggestions the Sportsbook's search box offers while a user types: players, teams and competitions that match the prefix.' An agent knows exactly what this returns and how it differs from a full search.

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?

Clearly routes the agent to a follow-up step: 'Use `search/tabs` for the full results of a chosen suggestion.' The primary usage context (user typing a prefix) is explicit, though it doesn't contrast with the sibling `fanduel_sportsbook_search` when no prefix typing is involved.

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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