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HaterPicks API

Find the best price for a market

get_best_price
Read-onlyIdempotent

Which Australian bookmaker pays the most for each side of a market: the best decimal price, the bookmaker, how many books price that side and how much more the best pays than the worst (spread_pct). Sharp reference books that cannot be backed are left out. Free keys cover game lines; player props need Starter or higher. Works on every plan, Free included. Counts as one API call (GET /api/v1/odds?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>",
      "search": "<search>"
    },
    "name": "get_best_price"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many rows to return (default 10, at most 50). Use search or market to narrow first.
sportYesSport code, upper case. list_sports_and_bookmakers lists every code and its markets.
marketNoA market key such as AFL_H2H or NBA_POINTS, or just its ending: H2H, TOTAL, LINE, SPREAD, POINTS, DISPOSALS.
searchYesTeam, player or matchup words, e.g. "Carlton" or "Nick Daicos". Every word must match.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive, and openWorld, so the safety profile is covered. The description adds genuinely incremental behavior: exclusion of unbackable sharp books (which affects result completeness), plan-based gating of player props, and the cost model ('Counts as one API call (GET /api/v1/odds?sport=)'). It stops short of describing pagination or how ties in best price are broken.

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?

The most valuable content — what is returned per side — is front-loaded in the first sentence, followed by scope caveats and plan tiers. It is dense but every sentence carries information (exclusions, tiers, cost), though the parenthetical endpoint string is marginal for an agent selecting the tool.

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?

There is no output schema, so the description carries the burden of explaining return values, and it does so field-by-field. Access-tier constraints and the sharp-book exclusion are both covered, which is unusual thoroughness. Missing only error/empty-result behavior (e.g. what happens when no books price a side), which keeps it below a 5.

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 description coverage is 100%, with all four parameters documented inline (including the market-key shorthand and search word-matching rules), so the baseline is 3. The description adds essentially nothing parameter-level beyond echoing the sport query string, so no credit above baseline is warranted.

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 states a specific question the tool answers ('Which Australian bookmaker pays the most for each side of a market') and enumerates the returned fields: best decimal price, bookmaker name, number of books pricing the side, and spread_pct versus the worst price. It also carves out a scope exclusion ('Sharp reference books that cannot be backed are left out'), which is a distinguishing trait. It never names get_odds or get_arbitrage directly, so sibling differentiation is inferred rather than explicit.

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?

The description gives access-tier guidance ('Free keys cover game lines; player props need Starter or higher') and notes the tool works on every plan, which tells an agent when calls will succeed. However, it offers no guidance on when to choose this over get_odds, get_arbitrage, or get_ev, leaving the agent to infer the distinction from returned fields.

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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