Data Masking Skill

Overview

Data Masking works by scanning text for sensitive data patterns and replacing them with masked placeholders. Returns both the masked text and detection statistics for multiple data types.

Live Test Data Masking Skill Skill →

The tool

Once your client is connected to the VerveKit server, this appears in its tool list as DataMaskingSkill. It is read-only and open-world — it fetches and never mutates anything on your side — so most clients call it without asking you to confirm.

Tool call

{
  "name": "DataMaskingSkill",
  "arguments": {
    "text": "Contact John at [email protected] or call 555-123-4567"
  }
}

You do not name the tool yourself; the model picks it. Asking about Contact John at [email protected] or call 555-123-4567 in the terms this skill covers is enough for it to reach for DataMaskingSkill on its own — naming it explicitly also works, and is the way to force the call.

Connecting

One server URL covers every skill in the catalog, including this one. Authorization is OAuth: the client opens a browser once, and there is no key to paste into a config file.

{
  "mcpServers": {
    "vervekit": {
      "url": "https://api.vervekit.com/v1/mcp"
    }
  }
}

Per-client setup — Claude, Cursor, VS Code, ChatGPT — is on the MCP setup page.

Arguments

These are the properties on the tool's inputSchema, so a well-behaved client validates them before the call is made. Premium arguments are accepted on every plan but only take effect on plans that include them.

Argument	Type	Description
`text`Required	string	The text containing sensitive data to mask length 0–50000
`types`OptionalPremium	array	Array of data types to mask (default: all types) default ["email","phone","ssn","credit_card","ip_address","url","date"]

What the model gets back

The result carries a structuredContent object matching the tool's declared outputSchema, so a client reads fields without parsing prose. status is "ok" and error is null on success; a null field means the value was not available for that input, not that the call failed.

Result

{
  "status": "ok",
  "error": null,
  "data": {
    "masked": "Contact John Doe at [EMAIL] or call [PHONE]. His SSN is [SSN].",
    "detected": {
      "email": 1,
      "phone": 1,
      "ssn": 1,
      "credit_card": 0,
      "ip_address": 0,
      "url": 0,
      "date": 0
    }
  }
}

Response fields

Paths are relative to data. Premium fields are absent rather than zeroed on plans that do not include them, so check for presence instead of comparing to 0.

Field	Type	Example	Description
`masked`	string	`Contact John Doe at [EMAIL] or call [PHONE]. His SSN is [SSN].`	Text with sensitive data replaced by masking placeholders
`detected`	object	`{…}`	Object containing count statistics for each detected data type
`detected.email`	number	`1`	Number of email addresses detected and masked in text
`detected.phone`	number	`1`	Number of phone numbers detected and masked in text
`detected.ssn`	number	`1`	Number of social security numbers detected and masked in text
`detected.credit_card`	number	`0`	Number of credit card numbers detected and masked in text
`detected.ip_address`	number	`0`	Number of IP addresses detected and masked in text
`detected.url`	number	`0`	Number of URLs detected and masked in text
`detected.date`	number	`0`	Number of dates detected and masked in text

Failure modes

Errors come back as tool errors carrying a sentence the model can act on, not a bare status code. Error handling covers the full list.

Status	What it means
`400` / `422`	The arguments did not validate. The message names the offending one.
`401`	The OAuth session is invalid or expired — reconnect the server.
`403`	Blocked by a key restriction or an IP allow-list. Never a bad identity.
`404`	This skill is not part of VerveKit. Check the catalog.
`429`	Out of credits, or a brief rate limit. The message tells them apart.

A call costs 10 credits each time the tool actually runs; a model that reasons about the tool without calling it costs nothing.

Use cases

GDPR Compliance: Automatically mask PII in logs, documents, and communications to comply with GDPR and privacy regulations
Data Anonymization: Anonymize sensitive customer data in datasets before sharing with third parties or using for testing
Log Sanitization: Remove sensitive information from application logs and error messages before storing or analyzing
Content Moderation: Mask sensitive data in user-generated content, support tickets, or public forums to protect privacy

Other ways to use Data Masking Skill

Set up Data Masking Skill on VerveKit, or reach the same source a different way. Your VerveKit account and credits work on all of them — one key, one balance.

Call it as a REST APIOne HTTPS endpoint and an x-api-key header, with SDKs for Node, Python and .NET.APIVerve →Reference →

Google Sheets or ExcelA =VERVE() formula fills a column — no script, no export, recalculates in place.VerveSheets →Reference →