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Generate a fake email

generate_email
Read-only

Need test data? Generate a synthetic email address for testing and mock workflows, with an optional name to personalize it.

Instructions

Generates a synthetic email address.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.0.0
    • removedInput schema / properties / name / description
      Removed value: -"The name of the email data"
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "value": {}
      +  },
      +  "required": [
      +    "value"
      +  ],
      +  "type": "object"
      +}
  2. First observedv1.0.1

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds the word 'synthetic' but provides no additional behavioral details (e.g., randomness, format, or how it interacts with the name parameter). It is consistent with annotations but adds minimal context.

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, direct sentence with no filler. It front-loads the purpose and wastes no words, achieving ideal conciseness for a simple tool.

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, the description is mostly sufficient for calling the tool, but the missing parameter semantics and lack of usage context leave it incomplete. It is adequate for a trivial generator but not fully self-contained.

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 description must explain the optional 'name' parameter, but it does not mention it at all. An agent cannot know what the name does or how to use it, leaving a critical gap for a parameter that could affect generation.

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 verb ('generates') and resource ('synthetic email address'), clearly distinguishing it from siblings like generate_person or generate_name. The title reinforces this, and the wording is not a tautology.

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 given about when to use this tool vs alternatives. The description does not mention any criteria, conditions, or exclusions, nor does it reference sibling tools. The agent is left to infer usage solely from the name, which is insufficient.

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