Skip to main content
Glama
debanshd

Tavily Web Search MCP Server

by debanshd

roll_dice

Simulate dice rolls using standard notation to generate random numbers for games, probability calculations, or decision-making scenarios.

Instructions

Roll the dice with the given notation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notationYes
num_rollsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • server.py:19-24 (handler)
    The MCP tool handler for 'roll_dice', decorated with @mcp.tool(), which instantiates DiceRoller with parameters and returns its formatted string result.
    @mcp.tool()
    def roll_dice(notation: str, num_rolls: int = 1) -> str:
        """Roll the dice with the given notation"""
        roller = DiceRoller(notation, num_rolls)
        return str(roller)
  • Core helper method in DiceRoller class that parses dice notation (e.g., 2d20k1), rolls the dice, sorts descending, keeps highest N, and returns all rolls and kept rolls.
    def roll_dice(self):
        match = self.dice_pattern.match(self.notation)
        if not match:
            raise ValueError("Invalid dice notation")
    
        num_dice = int(match.group(1))
        dice_sides = int(match.group(2))
        keep = int(match.group(4)) if match.group(4) else num_dice
    
        rolls = [random.randint(1, dice_sides) for _ in range(num_dice)]
        rolls.sort(reverse=True)
        kept_rolls = rolls[:keep]
    
        return rolls, kept_rolls
  • Helper method that performs the actual rolling (single or multiple) and formats the output string consumed by the tool handler.
    def __str__(self):
        if self.num_rolls == 1:
            rolls, kept_rolls = self.roll_dice()
            return f"ROLLS: {', '.join(map(str, rolls))} -> RETURNS: {sum(kept_rolls)}"
        else:
            results = self.roll_multiple()
            result_strs = []
            for i, result in enumerate(results, 1):
                result_strs.append(f"Roll {i}: ROLLS: {', '.join(map(str, result['rolls']))} -> RETURNS: {result['total']}")
            return "\n".join(result_strs)
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions rolling dice but fails to explain key behaviors: whether results are random, if there are constraints on notation or num_rolls, what the output looks like, or any error handling. This leaves significant gaps for a tool that likely involves randomness and input validation.

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 a single, efficient sentence with no wasted words. It's front-loaded with the core action and directly ties to the input, making it easy to scan and understand at a glance.

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

Completeness3/5

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

Given the tool's low complexity and the presence of an output schema (which should cover return values), the description is somewhat complete for basic use. However, with no annotations and poor parameter semantics, it lacks details on behavior and input handling, making it minimally adequate but with clear gaps for reliable tool invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It references 'notation' but doesn't explain its format (e.g., standard dice notation like '3d10') or purpose. It ignores 'num_rolls' entirely, leaving users to guess its role. This adds minimal value beyond the schema's basic property names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the action ('Roll the dice') and references the input parameter ('with the given notation'), which clarifies the basic purpose. However, it's vague about what 'notation' means (e.g., dice notation like '2d6') and doesn't distinguish this tool from any hypothetical sibling dice tools, though none exist in the provided list.

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 doesn't mention any prerequisites, context for rolling dice, or comparisons to other tools like random number generators. Without such information, users must infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/debanshd/AIE7-MCP-Session'

If you have feedback or need assistance with the MCP directory API, please join our Discord server