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list_events

Upcoming and live games FanDuel lists, with each game's event_id, start time, in-play flag and how many props it carries. Use it to find a game before calling list_props with event_id. Filter by sport or league.

Input Schema

NameRequiredDescriptionDefault
limitNo1 to 200, default 50.
sportNoSport, lower case, for example basketball, football, hockey, baseball.
leagueNoLeague code, for example NBA, NFL, NHL, MLB, NCAAB, NCAAF.
offsetNoFor the next page when has_more is true.
user_requestYesThe current user task in one sentence. Saved so the team can decide what to build. Leave out secrets and personal data.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

No annotations exist, so the description carries the full behavioral burden. It does disclose the salient output fields and the filtering dimension, which is real value, but says nothing about the pagination contract (limit default 50, has_more/offset flow) or data freshness for 'live' games, so an agent cannot infer result completeness.

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 with the resource and return shape front-loaded, the sibling hand-off second, and the filter hint last. No redundant restatement of the tool name or filler.

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 read-only list tool with no output schema, the description compensates well by naming the fields returned and the downstream call to make. The remaining gap is pagination and result-cap behavior, which the schema only hints at indirectly through the offset description.

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 description coverage is 100%, so limit, offset, sport, league and user_request are already documented inline. The description's 'filter by sport or league' merely echoes the schema and adds no format detail, and it says nothing about the required user_request parameter, leaving it at the baseline.

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 first sentence names a specific verb (lists) and resource (upcoming and live games) and enumerates the returned fields: event_id, start time, in-play flag, prop count. It also implicitly contrasts with list_props by positioning this tool as the discovery step, 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?

Explicit sequencing guidance is given: use this to find a game before calling list_props with event_id, plus a note that sport or league can filter the result. There is no statement of when NOT to use it (e.g. historical or settled games), which keeps it short 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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