HaterPicks API

Get player props

get_player_props

Read-onlyIdempotent

Player-prop markets for one sport across Australian bookmakers: player, market, line and each bookmaker's over and under price. Narrow with player, team and market. Needs the Starter plan ($29 AUD a month) or higher. Free keys can read sport nba from a copy refreshed every 30 minutes. Counts as one API call (GET /api/v1/props?sport=).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "sport": "<sport>"
    },
    "name": "get_player_props"
  }
}

Input Schema

Name	Required	Description
`team`	No	Team or matchup words, e.g. "Collingwood".
`limit`	No	How many rows to return (default 25, at most 100). Use search or market to narrow first.
`sport`	Yes	Sport key, lower case.
`market`	No	A market key such as AFL_H2H or NBA_POINTS, or just its ending: H2H, TOTAL, LINE, SPREAD, POINTS, DISPOSALS.
`player`	No	Player name words, e.g. "Daicos". Every word must match.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, and the description layers on genuinely new operational context the annotations cannot convey: a paid plan gate (Starter $29 AUD/month), a free-key restriction to sport nba with a 30-minute refresh staleness window, and quota consumption ('counts as one API call'). Those are exactly the auth, rate-limit and cost traits an agent needs before calling.

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?

Four compact sentences, with the highest-value content (what it returns, how to narrow) front-loaded, followed by plan and quota caveats. The pricing detail ('$29 AUD a month') is slightly verbose for an agent but no sentence is 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?

With no output schema, the description correctly compensates by enumerating the returned fields (player, market, line, over/under prices). Combined with the quota and plan-access caveats it covers calling prerequisites well; only minor gaps remain, such as what happens for non-nba sports on a free key or how large result sets paginate beyond the limit parameter.

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 all five parameters including the sport enum and the limit default/max. The description's 'narrow with player, team and market' restates what the schema says without adding format or matching semantics (e.g. that every player word must match — that detail lives in the schema). Baseline 3 is correct.

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?

States a specific verb+resource pair ('player-prop markets for one sport') and enumerates the returned fields (player, market, line, bookmaker over/under prices), which lets an agent distinguish this from get_odds or get_best_price by scope. It stops short of explicitly naming the sibling alternatives, so differentiation relies on inference from the sport-wide prop framing.

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

Usage Guidelines3/5

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

'Narrow with player, team and market' gives narrowing advice but is phrased as parameter guidance rather than when-to-use guidance. There is no explicit statement of when to prefer this over get_odds or get_best_price, and no exclusion such as 'use get_best_price for a single market comparison' — usage context is only implied.

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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