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BACH-AI-Tools

Calculator MCP

logarithm

Calculate logarithms for any number with custom base options. Use this mathematical tool to compute logarithmic values for scientific, engineering, or educational applications.

Instructions

对数计算

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYes真数
baseNo底数(可选,默认为 e)
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. '对数计算' only states the operation without explaining behavioral traits such as error handling (e.g., for negative numbers or base=1), computational limits, 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single phrase '对数计算', which is extremely concise and front-loaded. However, it's under-specified rather than efficiently informative, as it lacks necessary details. It earns a 4 for brevity but loses points for not using its minimal space effectively.

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 no annotations, no output schema, and a simple mathematical tool with 2 parameters, the description is incomplete. It doesn't explain the return value (e.g., a numeric result), error conditions, or how it differs from sibling tools. This leaves significant gaps for an agent to use it correctly.

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

Parameters3/5

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

Schema description coverage is 100%, with clear parameter descriptions in Chinese ('真数' for number, '底数(可选,默认为 e)' for base with default e). The description adds no meaning beyond the schema, but the schema does the heavy lifting, so the baseline score of 3 is appropriate.

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

Purpose2/5

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

The description '对数计算' (logarithm calculation) restates the tool name 'logarithm' in Chinese, making it a tautology. It doesn't specify what kind of logarithm calculation (e.g., natural log, base-10, custom base) or distinguish it from sibling tools like 'calculate' or 'factorial'. The purpose is vague beyond the obvious mathematical operation.

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

Usage Guidelines1/5

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 'calculate' (which might handle general math) or other mathematical siblings. The description offers no context, exclusions, or prerequisites, leaving the agent with no usage instructions.

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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