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flash-props-api

by io.github.iFan6oy

Season baselines, recent form, and context for a player

get_player_context

Season context from the sport's registered Flash pack: per-market baselines, recent form, and sport-native splits. Free and Starter receive the same basic context shape as REST; Pro adds the dense recent map/game log when available. If the sport has no registered pack or the player is unmatched, returns an honest empty context, never fabricated data. Use list_sports first when you need to discover which sports currently advertise deep context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesPlayer name or gamertag. Exact match is preferred; no invented identity mapping.
sportNoSport id. Use list_sports to discover contextCapability. Defaults to cod for backward compatibility.

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does well: it discloses tier differences (Free/Starter vs Pro), the empty-context fallback, and the never-fabricate guarantee. It stops short of covering error/rate-limit behavior, but the key trust-related traits are transparent.

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?

Four sentences, each earning its place: what the tool returns, tier differences, empty-response honesty, and the list_sports prerequisite. The core purpose is front-loaded and no filler is present.

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?

Given two params, no output schema, and no annotations, the description supplies enough context for an agent to select and invoke the tool: return shape, fallback behavior, and discovery path. It is not exhaustively detailed about output structure, but it is sufficient for this tool's complexity.

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 the schema already documents name and sport clearly. The description adds contextual flavor about registered packs and sport-native splits, but it does not materially add meaning beyond the schema's parameter descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource ('player context'), the source ('registered Flash pack'), and the contents (baselines, recent form, splits). It is specific enough to be understood, though it does not explicitly differentiate from sibling prop-scoped tools like find_player_props.

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?

Gives practical usage guidance: use list_sports first to discover sports with deep context. It also implies the tool is the right choice for season-context lookups, but it does not enumerate alternatives or exclusion conditions relative to sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All flash-props-api toolsInspect
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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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