UK Data for Agents

generate_username

Read-onlyIdempotent

Generates a unique username by combining first name, last name, and birth year with a random suffix using a cryptographically secure random source. (cost: 1 credit)

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

Name	Required	Description
`last_name`	No	string, required, user's last name, no units, no default
`birth_year`	No	integer, required, user's birth year, year, no default
`first_name`	No	string, required, user's first name, no units, no default

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 7, 2026

TDQS

C2.9/5.0

Behavior2/5

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

The description adds real value beyond the annotations by disclosing the randomness source (cryptographically secure) and a per-call cost of 1 credit, which the annotations do not cover. However, it explicitly describes a random, non-deterministic result, which conflicts with the annotation idempotentHint=true, and it does not say whether uniqueness is checked against an existing namespace or what the returned value looks like.

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 carries the mechanism, and the credit cost is tucked into a short parenthetical at the end. Nothing is wasted, though the sentence is long enough that the composition rule and the randomness claim run together.

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?

For a simple three-parameter, read-only generator with no output schema, the description covers the inputs and the generation mechanism. It still leaves open what is returned (a bare string? an object with the suffix?), how collision avoidance works, and whether the credit is charged on failure — all things an agent needs since no output schema exists to answer them.

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 coverage is 100%, so all three parameters are already documented in the schema, and the description merely restates the same fields it consumes. It adds no format details beyond the schema — for example, whether birth_year is a four-digit string or how non-ASCII names are transliterated — which matters given the schema declares birth_year as a string while describing it as an integer.

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?

The description names a specific verb and output ('Generates a unique username') and explains the exact composition rule (first name + last name + birth year + random suffix), so an agent knows precisely what it produces. It does not, however, contrast itself with the nearby siblings generate_random_string or generate_password, which also emit short strings.

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?

There is no guidance on when to choose this tool over generate_random_string, generate_password, or a hash-based approach; the only contextual detail is the 'cost: 1 credit' note. An agent must infer that a person's name and birth year are required inputs before it can decide this is the right generator.

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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