APIVerve

Username Profanity

UsernameProfanity

Read-only

Username Profanity: Username Profanity flags offensive or inappropriate usernames before they reach your database. Send any candidate handle to receive a clear true or false profanity check result; paid plans add the matched words and categories, reserved-name and contact-detail checks, a masked version of the username and a single allowed verdict. (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": {
      "username": "<username>"
    },
    "name": "UsernameProfanity"
  }
}

Input Schema

Name	Required	Description	Default
`username`	Yes	The username to check if it is inappropriate or profane

Output Schema

Name	Required	Description
`data`	No
`error`	No	Error message, null on success
`status`	No	"ok" on success

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 7, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and non-destructive behavior, so the description's job is lighter. It adds genuinely useful behavior beyond them: the 2-credit cost, the base true/false return, and the tier-dependent extras (matched words, categories, reserved-name/contact checks, masked username, allowed verdict). It doesn't state rate limits or error behavior, keeping it from a 5.

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?

Purpose is front-loaded in the first sentence, with output shape and cost in the second. The enumeration of paid-plan fields is somewhat dense but each item is informative; little is wasted.

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?

For a one-parameter, read-only check with an output schema and annotations, the description covers purpose, return shape, and cost, which is most of what an agent needs. It is slightly incomplete on how it relates to ProfanityFilter/ContentFilter when the agent must pick among siblings.

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% with a single well-described 'username' parameter, so baseline is 3. The description's 'send any candidate handle' echoes the schema rather than adding syntax, length, or encoding constraints for the input.

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 and resource: 'flags offensive or inappropriate usernames,' with the added context that this happens 'before they reach your database.' An agent can tell this is a username-validation check. It does not explicitly distinguish itself from the sibling ProfanityFilter (general text) or ContentFilter, so it falls short of a 5.

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

Usage Guidelines3/5

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

'Send any candidate handle' implies the use case is pre-registration validation, and the paid-plan clause hints at richer results, but there is no explicit when-to-use guidance and no exclusion pointing to ProfanityFilter for free-text content. Usage is inferable rather than stated.

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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