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mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

exp

Calculate the exponential of a numeric value with optional precision control.

Instructions

Compute exponential.

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": {
      "x": "<x>"
    },
    "name": "exp"
  }
}

Input Schema

NameRequiredDescriptionDefault
xYesNumber.
precisionNoOptional precision.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are present, so the description must carry the burden. It discloses no behavioral traits such as input domain, handling of edge cases (e.g., very large numbers), or the effect of the optional precision parameter.

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 very concise (2 words). While it is front-loaded and efficient, it may be too brief for an AI agent to fully understand the tool's behavior.

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 simplicity of the tool (computing exponential) and no output schema, the description is moderately complete. However, it lacks details about the base, domain, and precision behavior, which could help an agent use it effectively.

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?

The input schema has 100% coverage, describing 'x' as 'Number.' and precision as an optional integer. The description adds no additional meaning beyond the schema. Hence, baseline score of 3 is appropriate.

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

Purpose4/5

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

The description 'Compute exponential' clearly states the action and resource. However, it does not specify the base (natural exponential or general exponent?), which could cause ambiguity. It is distinct from siblings like 'log', 'sqrt', etc.

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 vs. alternatives. For example, there is no distinction between 'exp' and other exponentiation functions (e.g., power, pow) that might be relevant.

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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