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kelseyee

Calculator MCP

by kelseyee

power

Calculate power operations by raising a base number to an exponent. Use this tool to perform exponentiation for mathematical calculations.

Instructions

计算幂运算

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseYes
exponentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'power' tool, decorated with @mcp.tool(). It computes base raised to the power of exponent using the ** operator.
    @mcp.tool()
    def power(base: float, exponent: float) -> float:
        """计算幂运算"""
        return base ** exponent
Behavior1/5

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. '计算幂运算' only states the operation without any information on error handling, performance, mathematical constraints (e.g., large exponents), or output format. This is inadequate for a tool with no annotation coverage.

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 extremely concise with a single phrase ('计算幂运算'), which is appropriately sized for a simple mathematical tool. It is front-loaded with the core purpose and has zero wasted words.

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

Completeness2/5

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

Given the tool's mathematical nature and the presence of an output schema (which handles return values), the description is incomplete. It lacks context on usage, parameters, and behavioral traits, making it insufficient for an agent to fully understand when and how to invoke it correctly.

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

Parameters1/5

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

Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description adds no information about parameters beyond what the schema titles ('Base', 'Exponent') imply. For a tool with 2 parameters and 0% coverage, this is a significant gap.

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 '计算幂运算' (calculates power/exponentiation) states what the tool does with a clear verb+resource, but it doesn't distinguish from siblings like 'factorial' or 'sqrt' which are also mathematical operations. The purpose is understandable but lacks sibling differentiation.

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?

No guidance is provided on when to use this tool versus alternatives like 'multiply' for repeated multiplication or 'sqrt' for square roots. The description offers no context, prerequisites, or exclusions for usage.

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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