Hopi

Dummy data generator

hopi_dummy_data_generator

Read-onlyIdempotent

Generate fake but safe UK test records. Phone numbers come from Ofcom's reserved drama ranges and emails use RFC 2606 example domains, so no record can reach a real person. Returns an array of records, plus CSV text. Source: https://hopi.co.uk/dummy-data-generator/

Input Schema

TableJSON Schema

Name	Required	Description	Default
`count`	Yes	How many records to generate, from 1 to 1000
`fields`	No	Which fields to include (default all). Choose from firstName, lastName, fullName, email, ukMobile, ukLandline, streetAddress, town, postcode, dateOfBirth, company

Output Schema

TableJSON Schema

Name	Required	Description
`csv`	No
`rows`	No
`count`	No
`fields`	No
`summary`	Yes
`source_url`	Yes	The tool's page on hopi.co.uk (cite or open to check the figure)

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 20, 2026
- addedOutput schema / required
```
Added value: +[
+  "source_url",
+  "summary"
+]
```
First observedSep 20, 2026

TDQS

A4.2/5.0

Behavior4/5

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

The description adds valuable behavioral detail beyond the readOnly/idempotent/destructive annotations: phone numbers use Ofcom reserved drama ranges, emails use RFC 2606 domains, and it states the return shape (array plus CSV). This gives an agent confidence that the generated data is safe to use.

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 compact and well-structured: core purpose first, then concrete safety behavior, output format, and a source link. Every sentence adds useful information with no filler.

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

Completeness4/5

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

For a two-parameter tool with a full schema and output schema, the description covers the essential context: what is generated, why it is safe, and what format is returned. A minor gap is that it does not state whether generated data is random/deterministic or that fields default to all when omitted, though the schema covers the default.

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 count and fields clearly explained in the input schema. The description adds no param-specific detail, but it does not need to since the schema fully documents the parameters.

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 clearly identifies a specific operation: generate fake but safe UK test records. This distinguishes it from sibling generators that produce single values such as usernames or random numbers.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'fake but safe UK test records' makes the intended use obvious: creating dummy data for testing without risking contact with real people. It does not explicitly name alternatives or exclusions, but the context is clear.

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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