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bb-gnubg-mcp

bb-gnubg-mcp

by hbomze
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

roll

Simulate a backgammon dice roll, returning the value of each die.

Instructions

Simulate a roll of two six-sided dice.

Returns: Dict with die1 and die2 values (1-6 each).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "roll"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It explicitly states the action (simulate) and the exact return structure (dict with die1 and die2, each 1-6). This is sufficient for a simple, side-effect-free tool, though it does not explicitly mention randomness.

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 two sentences, immediately states the action, and includes the return format. There is no extraneous information, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, deterministic return shape) and the existence of an output schema, the description fully covers the necessary context. It specifies exactly what is returned, leaving little room for ambiguity.

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?

The tool has zero parameters and the schema is empty, so the baseline for 0-parameter tools is 4. The description adds relevant return semantics beyond the schema, though no parameter explanations are needed.

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 clearly states the tool simulates a roll of two six-sided dice, with a specific verb and resource. It is distinct from sibling tools like 'rollout' and 'cubeful_rollout', which refer to deeper simulation processes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention that this is for a simple random dice roll as opposed to rollout or other sampling tools.

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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