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flash-props-api

by io.github.iFan6oy

Get player props for a specific game

get_game_props

Fetch all player props for one game identified by eventId. Read-only. No side effects. Requires an API key; rate-limited per your tier. Returns: { eventId, sport, homeTeam, awayTeam, startTime, props: Array<{ player, stat, line, overOdds, underOdds, bookCount, gameState?, flashProjection? }>, sources: string[], fetchedAt, delayed }. flashProjection is present when that sport + market has a registered Flash model and a player baseline is available; it is { value, sampleN, method, marketKey } and is never fabricated. overOdds and underOdds are American-format integers (e.g. -110, +115); null when odds are not available. The stats parameter filters to specific markets (e.g. "points,rebounds" for basketball, "strikeouts,hits_allowed" for MLB). Typical workflow: (1) call list_games to get eventIds, (2) call get_game_props with the eventId. Alternatively, call find_game with team names to resolve the eventId when you know the matchup. Event ids are prefixed ud- (Underdog Fantasy source) or bv- (Bovada source). Returns an error when the event id is not found, the game has ended with no active props, or lines have not been posted yet. When to use: when you have an eventId and want all props for that specific game. When not to use: use scan_props instead when you want a cross-game market view. Use find_player_props when you know the player name but not which game they are in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sportNoSport id. Must match the sport the event belongs to. Omit to use the current in-season sport.
statsNoComma-separated list of stat keys to return, e.g. "points,rebounds,assists" for basketball or "strikeouts,hits_allowed" for MLB. Omit to return all available markets.
eventIdYesEvent id from list_games or find_game. Prefixed ud- or bv-, e.g. "bv-26839935" or "ud-119284".

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 meets it: 'Read-only. No side effects. Requires an API key; rate-limited per your tier.' It also documents error conditions, defensive guarantees (flashProjection is never fabricated), and value formats (American-format odds, null when unavailable).

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 long but every sentence earns its place: core purpose, safety/rate-limit behavior, return shape, parameter guidance, workflow, and explicit exclusions. It is front-loaded with the main action and scopes later remarks to edge cases and alternatives rather than repeating the schema.

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?

Since there is no output schema, the description fully documents the return shape and key field semantics, including the conditional flashProjection object and null odds. It also covers error conditions and prerequisite eventId resolution, making the tool callable without external docs. Minor fields like sources and delayed are named but their meaning is inferable.

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 context beyond the schema: eventId prefix examples ('bv-26839935'), the sport omission default ('current in-season sport'), and concrete stat-market examples for basketball and MLB, which helps an agent form valid parameter values.

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 opens with a specific verb and resource: 'Fetch all player props for one game identified by eventId.' It clearly distinguishes itself from siblings by naming scan_props and find_player_props as alternatives for different use cases, so an agent can select this tool without ambiguity.

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: when you have an eventId and want all props for that specific game' and 'When not to use' with specific sibling tools (scan_props, find_player_props). It also provides a typical workflow pairing list_games or find_game with get_game_props, leaving nothing to inference.

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.

Resources