Generate fake person data including names, emails, phone numbers, and addresses for testing. Set locale and quantity to produce sample user records.
Generate fake person data (name, email, phone, address) for testing.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Locale code (default: en_US). | |
| quantity | No | Number of persons (max 100, default 5). |
Changes observed during successful MCP inspections.
v0.1.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It says what is generated but does not clarify randomness, side effects, safety, or return structure beyond a brief field list.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence states the action, output fields, and testing context. There is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple generator with fully documented inputs and no output schema, the description is mostly complete because it lists the generated fields. It could say more about the return shape, but the core information is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters fully. The description adds no parameter-level meaning beyond what the input schema provides, making the baseline score appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Generate fake person data,' and lists representative fields. It is clearly a person-data generator, though it does not explicitly distinguish itself from all similar sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'For testing' gives an implied usage context, but there is no guidance on when to choose this over alternatives or when not to use it. The intended testing scenario is present but underdeveloped.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.