DeepChamp for Agents

Expected value scan

calc_ev_scan

Read-onlyIdempotent

Expected value per unit for up to 50 price and probability pairs you supply. 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": {
      "items": "<items>"
    },
    "name": "calc_ev_scan"
  }
}

Input Schema

Name	Required	Description
`items`	Yes	Up to 50 price and probability pairs.
`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.
`min_edge_points`	No	Only flag items whose probability exceeds the implied probability by at least this many percentage points. Default 0.

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

A3.6/5.0

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 beyond them: nothing is stored, no outside data is read, the free/no-signup access model, and a hard cap of 50 pairs. The remaining text is compliance boilerplate (21+, problem-gambling line) that is appropriate for the domain but not behavioral disclosure.

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 core statement is front-loaded and correct, but roughly half the text is disclaimer boilerplate that repeats the same idea twice ('Research intelligence, not winning picks' and 'Research and information, not betting advice'). Those disclaimers are defensible in a gambling-adjacent tool, yet the repetition and the hotline line dilute an otherwise tight definition.

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?

An output schema exists, so return values need not be described, and the rich input schema covers parameters. The description supplies scope, the 50-item limit, the statelessness guarantee and the safety framing an agent needs to invoke it responsibly. Only the lack of explicit routing to sibling calculators is missing.

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% and the schema thoroughly documents items, price formats, probability bounds, visual, harness and min_edge_points. The description only restates the 50-pair ceiling and the per-unit framing. It adds no syntax or interpretation guidance the schema does not already carry, so the baseline 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 opening sentence names a concrete computation (expected value per unit) and its input (price and probability pairs you supply). It cleanly separates arithmetic on caller-supplied numbers from anything that reads outside data, which helps distinguish it from data-fetching or pricing-comparison siblings. It stops short of naming which sibling to use for adjacent jobs, so it is clear but not fully differentiated.

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?

Usage is implied by 'pairs you supply' and 'arithmetic on your own numbers only', which tells the agent this tool needs caller-provided prices and probabilities rather than internal lookups. There is no explicit when-not guidance and no named alternative for cases where the user lacks their own inputs. The agent must infer the boundary itself.

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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