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Human Name Parser

HumanNameParser
Read-only

Human Name Parser: Human Name Parser splits full name strings into first, middle, and last names, titles, nicknames, and suffixes. It also generates initials directly from the detected components. (Cost: 2 credits)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

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

Input Schema

NameRequiredDescriptionDefault
nameYesThe human name to parse

Output Schema

NameRequiredDescriptionDefault
dataNo
errorNoError message, null on success
statusNo"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful non-schema context by stating the credit cost (2 credits). However it discloses nothing about how ambiguous names are resolved, ordering assumptions, or locale handling, which is the main behavioral question for a name parser.

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?

Two functional sentences, front-loaded with the core operation, and the cost note is tucked at the end where it belongs. The only waste is the 'Human Name Parser: Human Name Parser' prefix, which repeats the name and title verbatim.

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?

With an output schema present, the description needn't explain return values, and for a one-parameter tool it covers the essentials. It falls short on input-format expectations and edge-case behavior (mononyms, comma-delimited names), which an agent would need to call it confidently.

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?

There is a single parameter with 100% schema description coverage and a concrete example ('MR. MARTINO PETROS DE FLORENCE (TINO) Jr.'), so the schema already carries the weight. The description reinforces which components can be returned but adds no syntax or format constraints beyond the schema. Baseline 3 is appropriate.

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 states a specific verb and resource ('splits full name strings') and enumerates the exact components extracted: first, middle, last, titles, nicknames, suffixes, plus initials. That is far more informative than the tautological title. It does not distinguish itself from any sibling, but no sibling in the list is a direct name parser, so the ambiguity cost is low.

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 when-to-use or when-not guidance, and no routing to alternatives such as StreetAddressParser, ContactExtractor, or RandomIdentityGenerator. The usage is only implied by the verb 'splits'. It also gives no guidance on acceptable input formats (e.g. 'Last, First' ordering or multi-token names).

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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