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flash-props-api

by io.github.iFan6oy

Resolve team names to an event id

find_game

Translate a matchup (home team + away team) into the eventId needed by get_game_props. Read-only. No side effects. Requires an API key; rate-limited per your tier. Use this when you know the teams playing but don't have the eventId. On success returns: { eventId }. Pass that id straight to get_game_props. On failure returns an error explaining that the game was not found on today's board. If multiple games match the team names (rare), returns the first match sorted by start time. Matching is case-insensitive substring containment against the full team name. When not to use: use list_games to browse a slate, or get_game_props directly if you already have the eventId.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
awayYesAway team name or city, matched the same way.
homeYesHome team name or city, matched as a case-insensitive substring of the full team name.
sportNoSport id. Omit to default to the current in-season sport.

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does an excellent job: it discloses read-only/no side effects, API key requirement, rate limiting, matching semantics, tie-breaking by start time, success payload shape, and failure behavior.

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?

The description is dense but every sentence earns its place: when to use, safety profile, success/failure behavior, matching semantics, and explicit alternatives. The most important purpose is front-loaded in the first sentence.

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?

Despite no output schema and no annotations, the description is complete enough for an agent to call the tool correctly: it covers input semantics, output format, edge cases with multiple matches, failure mode, authentication/rate limits, and routing to sibling tools.

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. The description adds meaningful semantic detail beyond the schema: case-insensitive substring containment, defaulting sport to the current in-season sport, and passing the resulting eventId directly to get_game_props.

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 uses a specific verb and resource: translating a home/away matchup into the eventId needed by get_game_props. It clearly distinguishes the tool from siblings by focusing on resolving team names to an ID rather than browsing or fetching props.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use the tool ('when you know the teams playing but don't have the eventId') and when not to use it, naming alternatives: list_games for browsing a slate and get_game_props if you already have the eventId.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource or access pattern: game lookup, game props, player props, cross-game scans, metadata, context, evidence, history, leaders, and movers. Related tools like list_games/find_game and scan_props/find_player_props are clearly separated by scope and reinforced with when-to-use guidance. No two tools appear to do the same job.

Naming Consistency5/5

All 12 tool names follow a consistent snake_case verb_noun pattern with a small set of meaningful verbs: find_* for lookups, list_* for catalogs, get_* for specific resources, and scan_* for cross-game views. There is no casing or verb-style mixing.

Tool Count5/5

12 tools is well within the ideal range and appropriate for the API's breadth: sports discovery, game discovery, multiple prop-access paths, market vocabulary, player context, evidence/history, and movement/leader boards. Each tool adds a distinct access pattern rather than redundant duplication.

Completeness5/5

The surface covers the full read-only workflow: discover sports, resolve games/eventIds, fetch props by game/player/cross-game, interpret market keys, and drill into context/evidence/history/movers/leaders. Tool outputs feed naturally into each other, so there are no obvious dead ends or missing operations for the stated domain.

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