random-mcp

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roll_dice

Roll dice expressions like 2d10 or 1d10 + 2d100 + 5d4, returning per-term subtotals and grand total. Choose full, compact, or auto detail for large rolls.

Instructions

Roll NdM dice or sums, such as 2d10 or 1d10 + 2d100 + 5d4.

Return count, sides, subtotal per term and a grand total. Full detail also includes every roll; compact omits rolls. Auto uses compact above 100 dice. Only addition is supported; no modifiers, subtraction, or parentheses. Limits: 10,000 total dice, 100 terms, 1,000,000 sides per die, and 10,000 expression characters.

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": {
      "expression": "<expression>"
    },
    "name": "roll_dice"
  }
}

Input Schema

Name	Required	Description	Default
`detail`	No		auto
`expression`	Yes

Output Schema

Name	Required	Description	Default
`terms`	Yes
`total`	Yes
`detail`	Yes
`expression`	Yes
`total_dice`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 15, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: it explains return values (count, sides, subtotal, grand total), detail-level behavior (full/compact/auto with auto threshold at 100 dice), support for only addition (no modifiers/subtraction/parentheses), and hard limits (10,000 dice, 100 terms, 1,000,000 sides, 10,000 characters). This is comprehensive and goes beyond what the schema reveals.

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 efficient and well-structured: it opens with the core purpose and an example, then explains return/behavior, then limits. Every sentence adds value, and there is no redundant information. It is front-loaded with the most critical information.

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?

For a tool with two parameters, an output schema, and clear limits, the description covers all necessary calling context: syntax, return content, detail modes, and constraints. The output schema handles the exact structure, so no additional return-format explanation is needed. An agent can confidently invoke this tool.

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?

Schema coverage is 0%, so the description carries the responsibility of explaining parameters. It thoroughly defines 'expression' with syntax and examples, and explains 'detail' enum values (auto, full, compact) and their behavioral meaning. This fully compensates for the schema's lack of descriptions.

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 states a specific action ('Roll NdM dice or sums') with concrete examples ('2d10', '1d10 + 2d100 + 5d4'). It clearly identifies the resource (dice expressions) and distinguishes itself from siblings like random_number, random_interval, and random_normal by focusing on dice-notation syntax.

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

Usage Guidelines4/5

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

The description implicitly communicates usage context through its detailed explanation of dice notation and supported operations. It does not explicitly name alternatives or exclusion criteria, but the clarity of its scope makes it obvious when to use this tool versus simple random-number generators. Slight gap: no explicit 'use this when...' guidance.

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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