bb-gnubg-mcp

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equities_value

Calculate match equity in backgammon by entering the points each player needs to win; receive player X's match winning chance.

Instructions

Look up match equity for a given match score.

Args: x_away: Points player X needs to win the match (0-25). o_away: Points player O needs to win the match (0-25).

Returns: Dict with match winning chance (MWC) for player X.

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": {
      "x_away": "<x_away>",
      "o_away": "<o_away>"
    },
    "name": "equities_value"
  }
}

Input Schema

Name	Required	Description	Default
`o_away`	Yes
`x_away`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 9, 2026

TDQS

A3.9/5.0

Behavior2/5

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

Without annotations, the description carries the full burden of behavioral disclosure. It states that the tool returns a dict with MWC but does not explicitly mention that it is a read-only operation, any side effects, or edge-case behavior for invalid score values. The verb 'look up' hints at read-only nature but is not explicit.

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

Conciseness5/5

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

The description is compact and well-structured, with a one-sentence purpose followed by Args and Returns sections. Every word is purposeful, and the format is easy to scan for both parameter semantics and return value.

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 simple lookup tool, the description covers the essential aspects: purpose, both parameters with ranges, and the return type. Since an output schema exists, detailed return documentation is not required. However, it omits any mention of error handling or invalid input behavior, which is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides no descriptions for its two integer parameters (schema description coverage is 0%). The description fully compensates by explaining the meaning of both parameters: x_away is points player X needs to win (0-25) and o_away is points player O needs to win (0-25), including valid ranges.

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 description opens with a specific verb 'Look up' and a clear resource 'match equity' given a match score, making its purpose immediately obvious. It distinguishes itself from sibling tools by focusing on match winning chance (MWC) for a player, which is a distinct concept from general probabilities or rollout results.

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 implies usage for computing match equity from a match score, but it does not explicitly state when to prefer this tool over alternatives like 'probabilities' or 'cubeful_rollout'. It provides clear input context but lacks exclusions or alternative tool references.

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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