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bb-gnubg-mcp

bb-gnubg-mcp

by hbomze
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

one_checker_race

Estimate win probability in a one-checker bearoff race by providing the pips remaining. Returns equity and standard deviation to help you assess the position.

Instructions

Estimate win probability for a one-checker bearoff race.

Args: pips: Number of pips remaining to bear off a single checker.

Returns: Dict with equity and standard deviation, or null if unsupported.

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": {
      "pips": "<pips>"
    },
    "name": "one_checker_race"
  }
}

Input Schema

NameRequiredDescriptionDefault
pipsYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries the transparency burden. It does disclose the return shape ('Dict with equity and standard deviation') and the null-if-unsupported behavior, which is helpful. But it does not explain what 'unsupported' means, how equity relates to win probability, or any assumptions/error behavior.

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 clear Args and Returns sections. Every sentence adds necessary information without filler.

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 tool with one parameter and an existing output schema, the description covers the key input and return behavior. It could be slightly more complete by clarifying the unsupported condition and what 'equity' means, but it is largely sufficient.

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 schema only says 'pips' is an integer, but the description adds meaningful semantics: 'Number of pips remaining to bear off a single checker.' This fully compensates for the 0% schema description coverage.

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 and resource: 'Estimate win probability for a one-checker bearoff race.' This precisely defines the tool's function and differentiates it from general bearoff tools like bearoff_probabilities and probabilities.

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 the phrase 'for a one-checker bearoff race,' which tells the agent when this tool is relevant. However, there is no explicit comparison to sibling tools, no 'when not to use,' and no alternative recommendations.

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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