olympus-bets-analytics

get_player_props

Read-onlyIdempotent

Return the live player-props board for NFL, MLB or WNBA (MCP Connect or Pro).

Requires ``Authorization: Bearer obmcp_...`` (MCP Connect — included with
website Premium — or MCP Pro). Free and anonymous callers are denied.

Each prop row carries: player, team, game, kickoff (America/New_York),
market, line, model projection, model over/under probability, the stored
best price and book (plus other books where the odds file stores them),
edge_pct, the model's pick side, confidence tier and units where the lane
produces them, whether it is on the lane's premium board, and
``lane_status`` — the factual verdict of that lane's promotion gate
(e.g. NFL ``research_board``, WNBA ``promoted_live``, MLB per market).
lane_status is information, not a filter: every row is returned.

Prices are exactly as stored by the odds pipeline; a missing price is
``null`` (never a placeholder). MLB rows come from the daily MLB props
export: the MLB ledger stores no pick side for player props, so
``pick_side`` is null and ``edge_pct`` is the stored OVER-side edge
(``edge_side: "over"``).

Args:
    league: ``nfl``, ``mlb`` or ``wnba`` (required).
    date: ``YYYY-MM-DD`` slate date in the live window — yesterday through
        7 days ahead (America/New_York); defaults to today. Earlier dates
        are resolved history: use ``get_player_prop_history`` (MCP Pro).
    game: Optional matchup/team filter (e.g. ``"NE@JAX"``, ``"JAX"``).
    player: Optional player-name filter (substring, accent-insensitive).
    market: Optional market filter (e.g. ``rush_yds``, ``points``,
        ``pitcher_ks``).
    limit: Max rows (1-200, default 100), sorted by edge_pct descending.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`date`	No
`game`	No
`limit`	No
`league`	Yes
`market`	No
`player`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 28, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations establish readOnly/idempotent, but the description adds substantial behavioral context they cannot: the auth gate that denies anonymous callers, the fact that lane_status is informational and does not filter rows, that missing prices are null (never placeholders), and the MLB quirk where pick_side is null and edge_pct is the stored OVER-side edge.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose then auth, and each section is functional. The row-field inventory is long, and since an output schema exists some of that enumeration is arguably redundant structural detail rather than semantics; the paragraph on lane_status and MLB edge handling, however, is genuinely non-derivable and earns its space.

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?

Covers auth, league/date/game/player/market/limit semantics, the sort order, and non-obvious return-value caveats (null prices, lane_status non-filtering, MLB pick_side null). With an output schema providing structure, nothing an agent needs to call this correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does so: enumerates league values, specifies the date format plus live-window bounds and today-default, gives game/team syntax examples, notes player matching is substring and accent-insensitive, lists market examples, and gives the limit range and edge_pct-descending sort.

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+resource+scope: return the live player-props board for NFL/MLB/WNBA, with the 'live window' constraint baked in. It is immediately distinguishable from the sibling get_player_prop_history, which it names explicitly for resolved history. No agent could confuse the two.

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?

Explicitly routes to get_player_prop_history for dates earlier than the live window, states the auth requirement (MCP Connect or Pro; free/anonymous denied), and gives concrete filter examples. When-to-use, when-not, and prerequisites are all present rather than inferred.

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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