bb-gnubg-mcp

by hbomze

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

key_of_board

Convert any backgammon board into its GNUBG position key string. Get a unique key for position analysis.

Instructions

Convert a board to its GNUBG position key string.

Args: board_input: Board in any supported format. player: Who is on roll ("x" or "o"). Required if board_input is a boardState dict.

Returns: Dict with the position key string.

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": {
      "board_input": "<board_input>"
    },
    "name": "key_of_board"
  }
}

Input Schema

Name	Required	Description	Default
`player`	No
`board_input`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 9, 2026

TDQS

A3.7/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It explains the conversion behavior and the conditional requirement for 'player.' However, it does not disclose potential error cases, format limitations, or other behavioral traits. This is adequate but lacks depth.

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 concise, with a clear one-sentence summary followed by an Args section and a Returns section. Every line adds value, and the structure is easy to scan. No wasted words.

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 conversion tool, the description covers the essential aspects: input format, player condition, and return value. The presence of an output schema reduces the need to detail the return structure. It doesn't enumerate supported formats, but that's a minor gap given the tool's simplicity.

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

Parameters4/5

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

With 0% schema description coverage, the description adds meaning beyond raw types: board_input is 'a board in any supported format,' and player is 'who is on roll' with a note that it's required for boardState dicts. This compensates well, though it could elaborate on what formats are supported.

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 clearly states the tool's function: 'Convert a board to its GNUBG position key string.' This specifies the verb (convert) and resource (board to position key). It doesn't explicitly distinguish from sibling tools like board_from_position_key, but the direction is clear, so it earns a 4 rather than 5.

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: if you need a key string from a board, use this tool. It provides a specific condition for the 'player' parameter ('Required if board_input is a boardState dict'), but does not explicitly discuss alternatives or when not to use the tool. This meets the minimum viable level.

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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