DeepChamp for Agents

Best price

calc_best_price

Read-onlyIdempotent

Rank up to 50 prices you supply for the same outcome by payout. Arithmetic on your own numbers only: nothing is stored and no outside data is read. Research intelligence (probabilities, factors, context), not winning picks. Price: Free, no signup. Research and information, not betting advice. No outcomes are guaranteed. Adults 21+ only, where legal. Problem gambling help: 1-800-MY-RESET.

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": {
      "options": "<options>"
    },
    "name": "calc_best_price"
  }
}

Input Schema

Name	Required	Description
`visual`	No	Optional. How to present the result: auto (default, chosen by client), image (picture and link), text (terminal chart), none (data only).
`harness`	No	Optional display hint. It changes the output format only, never access, price or limits.
`options`	Yes	Up to 50 prices for the same outcome.

Output Schema

Name	Required	Description
`data`	No
`meta`	No
`error`	No	Failure only: code, message, request_id, billable (always false).
`visual`	No
`billing`	No	Always free for the calculators: status free, price_micros 0.
`rest_url`	No
`compliance`	No
`continue_url`	No

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the bar is lower; the description still adds real value by stating nothing is stored, no outside data is read, the 50-item cap, and that it is free with no signup. It does not describe the ranking output, but an output schema exists to cover that.

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

Conciseness3/5

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

The functional content is front-loaded in two tight sentences, but roughly half the text is compliance boilerplate (21+, gambling helpline, no guaranteed outcomes) that does not help an agent select or invoke the tool. It is not padded with redundancy, but the signal-to-noise ratio is mediocre.

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 rich annotations, a 100%-covered schema and an output schema, the description only needs to establish purpose, constraints and cost, which it does. The remaining gap is the absence of any guidance on choosing between this and the other calc_* tools.

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%, so the schema already documents options, price formats, label pattern, visual and harness. The description only reinforces that all supplied prices must be for the same outcome, which the schema also states, so it adds little beyond the structured fields.

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?

The opening sentence gives a specific verb and resource ('Rank up to 50 prices you supply for the same outcome by payout') and the second sentence scopes it ('Arithmetic on your own numbers only: nothing is stored and no outside data is read'), which implicitly separates it from siblings that read external data such as get_daily_slate or get_matchup_context.

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 makes the use case clear (you have multiple prices for one outcome and want them ranked), but it never states when NOT to use it or names an alternative tool such as calc_parlay or calc_ev_scan. Usage is implied rather than routed.

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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