Skip to main content
Glama

Generate fictional people and company records

generate-fake-data
Read-onlyIdempotent

Create fictional users, companies, addresses or rows. Use to seed demos with preset records; use generate-dataset for custom fields. Synthetic values are not verified identities.

Input Schema

NameRequiredDescriptionDefault
kindYesFixture category: user, company, address or rows.
seedNoOptional deterministic seed to reproduce the same fake records.
countNoRequested number of synthetic records, up to eight.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds a genuinely useful caveat that output values are not verified identities, a trust/quality signal not present in structured fields. It does not mention the deterministic seed behavior beyond what the schema already states.

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?

Two compact sentences, front-loaded with the core action and followed immediately by routing and a caveat. Every clause earns its place with no redundancy.

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?

A simple, read-only, single-required-parameter tool with a fully documented schema and no output schema; the description covers purpose, alternative, and a data-trust caveat. It stops short of describing the shape of returned records, which is the only remaining gap for an agent consuming the output.

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%, so kind, seed, and count are fully documented in the schema, establishing the baseline of 3. The description's 'preset records' phrasing loosely implies the kind values are fixed fixtures, but it adds no syntax or semantics (e.g., seed determinism, the eight-record cap) beyond the schema.

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?

States a specific verb ('Create') and concrete resources ('fictional users, companies, addresses or rows') that map directly to the kind enum. It also names the sibling tool it is not (generate-dataset for custom fields), so an agent can distinguish it without opening either schema.

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

Usage Guidelines5/5

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

Gives both the use case ('seed demos with preset records') and the explicit alternative ('use generate-dataset for custom fields'), which is the exact selection condition an agent needs. Nothing is left to inference about when to pick this tool over its sibling.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources