HaterPicks API

Get +EV player-prop prices

get_ev

Read-onlyIdempotent

Player-prop prices where the best Australian bookmaker price beats the fair price, best edge first: player, stat, line, side, best price and bookmaker, edge % (market_ev_pct) and fair probability. basis says whether the fair price comes from our model and the market or the market alone. Needs the Pro plan ($79 AUD a month) or higher. Counts as one API call (GET /api/v1/ev).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_ev"
  }
}

Input Schema

Name	Required	Description
`limit`	No	How many rows to return (default 20, at most 100). Use search or market to narrow first.
`sport`	No	Only this sport, e.g. AFL or NBA (any case).
`min_edge_pct`	No	Only picks whose edge (market_ev_pct) is at least this percent.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 9, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive). The description adds genuinely non-structured detail: the plan gate, the exact cost of one API call with the endpoint path, the sort order (best edge first), and what 'basis' means for fair-price provenance. It omits pagination behavior beyond the limit parameter, which keeps it just short of a 5.

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 the core filtering condition, then field list, then 'basis' semantics, then plan and cost. Four dense sentences with no filler, though the returned-field enumeration is somewhat list-like and could be tightened.

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?

For a read-only, no-output-schema tool, the description does the work an output schema would: it enumerates the return fields and explains 'basis'. Cost and plan gating are also covered. Only pagination/response-shape mechanics are left unaddressed.

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 limit, sport, and min_edge_pct are already fully documented, including the useful 'use search or market to narrow first' note. The description reinforces what edge (market_ev_pct) means but adds no filter-combination or syntax detail beyond the schema, so the baseline of 3 applies.

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 definition names a specific resource (player-prop prices) and a precise filter condition (best Australian bookmaker price beats fair price), plus the sort order and returned fields. This differentiates it semantically from get_player_props and get_best_price, though it never names those siblings explicitly.

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?

It gives prerequisites (Pro plan, $79 AUD/month) and states the implicit narrowing advice in the schema ('use search or market to narrow first'), but the description itself never says when to pick this over get_arbitrage, get_best_price, or get_player_props. Usage is implied by the +EV filter rather than spelled out.

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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