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Profanity Filter

ProfanityFilter
Read-only

Profanity Filter: Profanity Filter is a bad word filter API that scans text for offensive language and masks detected swear words with a chosen replacement character. It returns the sanitized text and a boolean flag indicating if profanity was present. Paid plans add the count of filtered words, each matched word with its position, and custom allow and block word lists. (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": {
      "text": "<text>"
    },
    "name": "ProfanityFilter"
  }
}

Input Schema

NameRequiredDescriptionDefault
addNoComma-separated extra words to flag and mask, up to 100 single words
maskNoThe mask to replace the profanity words with. Should be a Single Character (e.g., *)*
textYesThe text to filter profanity words from
allowNoComma-separated words the filter should not flag, up to 100 single words (e.g. hell,damn)
detailsNoAdd a matches list with each filtered word and its start and end position

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

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered; the description adds genuinely non-obvious behaviour by explaining what comes back (sanitized text plus a boolean flag) and that counts, match positions, and custom allow/block lists are gated behind a paid plan. It also discloses a per-call cost of 2 credits, which no annotation provides. The only soft spot is that the 'block' list it mentions corresponds to no obvious schema parameter ('add' is described as extra words to flag).

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?

The most useful facts — what it does, what it returns, what costs credits — are front-loaded in a compact block. It loses a little to redundancy in the opening ('Profanity Filter: Profanity Filter is a bad word filter API'), which repeats the name twice before saying anything new.

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?

With an output schema present and full schema coverage, the description does not need to enumerate return fields, yet it still summarises them usefully, and it covers the cost/plan dimension that structured fields cannot express. It is only missing explicit sibling routing, which is a minor gap for a simple single-purpose text transformer.

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 description coverage is 100%, so all five parameters are already documented in the schema, and the baseline is 3. The description corroborates a couple of them (masking with a chosen replacement character, allow/block lists) but adds no format, limit, or interaction detail beyond what the schema states, and it muddies 'add' vs 'block' terminology.

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: it scans text for offensive language and masks detected swear words with a replacement character. That is far more specific than a name restatement, but the description never distinguishes it from near-neighbours like ContentFilter or UsernameProfanity, which an agent browsing this large catalogue will encounter.

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?

Usage is only implied by the purpose statement — an agent can infer 'call this to sanitize user-supplied text' but there is no explicit when-to-use, no exclusion conditions, and no pointer to competing siblings such as ContentFilter. The mention of cost (2 credits) and paid-plan gating is helpful context but is not selection guidance.

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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