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FauxGen MCP

FauxGen MCP

by LazyInvestor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Generate usernames

generate_username

Create fictional usernames in batches for testing profiles, sign-ups, or seed data. Set a count to receive up to 50 handles.

Instructions

Generate fictional usernames.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_username"
  }
}

Input Schema

NameRequiredDescriptionDefault
countNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full burden. It does not disclose output format, uniqueness guarantees, randomness/source, or determinism. 'Fictional' hints that data is synthetic, but that is thin behavioral context.

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?

A single, front-loaded sentence with no filler. It is efficiently written, though its brevity is partly a symptom of under-specification rather than disciplined conciseness.

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

Completeness2/5

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

For a simple one-param generator this could be adequate, but with no annotations, no output schema, and no parameter documentation, the description leaves the agent without return format, count semantics, or usage context. It is under-informative relative to the tool's role in a large generator family.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

One parameter (count) with 0% schema description coverage — no description in the schema either, and the tool description mentions no parameters at all. The default of 1, min 1, and max 50 are only visible in the schema; the description does nothing to explain or constrain count.

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?

States a specific verb (generate) and resource (fictional usernames), clearly distinguishing it from siblings like generate_email or generate_name. The 'fictional' qualifier is a meaningful scope cue. It does not, however, reference any specific sibling to reinforce differentiation.

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 when-to-use, when-not-to-use, or alternative guidance is provided. For a sibling set of ~17 generate_* tools, the description gives no signal about when a username is the right artifact versus generate_identity or generate_email.

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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