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Clotr Guard

Clotr Guard

Official
by clotr-app
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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Check text

check_text
Read-onlyIdempotent

Scans text for credentials and optional personal details before sharing, returning detected kinds and masked forms so you can review sensitive data without blocking workflows.

Instructions

Check text for credentials before it leaves this computer or goes to another tool. Returns kinds and masked forms, and blocks nothing.

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": "check_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
textYesThe text to check, up to 64 KiB.
include_personal_detailsNoAlso check personal details like emails. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description does add real value by disclosing that it only reports and 'blocks nothing' (no redaction, no enforcement) and that it returns masked forms. It doesn't mention performance, error behavior, or whether any logging occurs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with zero filler. The use-case trigger comes first and the return/behavior note second, which is the right order for an agent scanning for fitness.

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 no output schema, the description usefully states the return shape ('kinds and masked forms') and the critical non-blocking behavior. It is nearly complete for a simple two-parameter read tool, though 'kinds' is left unenumerated.

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 both parameters fully documented including the 64 KiB limit and the default for include_personal_details. The description adds no parameter-level detail beyond what the schema states, so the baseline applies.

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 gives a specific verb and resource: 'Check text for credentials'. It also signals the tool's non-enforcing nature ('blocks nothing'), which implicitly separates it from a redacting sibling like clean_text, though no sibling is named outright.

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

Usage Guidelines4/5

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

The trigger is explicit and concrete: run it 'before it leaves this computer or goes to another tool'. That covers the when. It stops short of naming alternatives (e.g. 'use clean_text to actually redact') or stating when-not to use it.

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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