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Generate fake name

generate_name

Create locale-aware first and last names by country and gender to seed realistic fictional identities and test users.

Instructions

Generate a locale-aware first/last name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genderNorandom
countryNoISO country code used on fauxgen.com. One of: us, gb, ca, au, nz, ie, in, pk, ng, za, gh, np, hk, ph, de, at, ch, fr, be, lu, es, mx, pt, br, it, nl, ru, by, kz, ua, pl, cz, sk, hu, ro, md, gr, tr, hr, si, rs, mk, bg, my, sg, se, no, dk, fi, lv, il, ae, sa, eg, ir, am, ge, az, jp, kr, cn, tw, th, vn, id, snus

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full disclosure burden, yet it says nothing about the return shape (single concatenated string vs. object), randomness, or determinism. For a generator with zero annotation coverage this is a real gap.

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 waste. It is appropriately sized, though its brevity comes partly from omitted information rather than pure efficiency.

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?

The tool is simple (2 optional params, no output schema, no nested objects), so a short description is defensible, but the return value and the meaning/effect of the gender parameter are never addressed, leaving real gaps.

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?

With only 50% schema description coverage, the description should compensate. It hints that country drives locale-awareness, but says nothing about the gender parameter (male/female/random) and adds no format detail beyond what the schema already declares.

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 (first/last name) with a qualifier (locale-aware). It is clear enough to distinguish from siblings like generate_email or generate_username, but does not explicitly call out the boundary.

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 statement of when to use this tool versus siblings such as generate_identity (which likely also yields names) or generate_username. Usage is only weakly implied by 'locale-aware'.

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