Regex Validator

Overview

You send a pattern; we compile it on the RE2/J engine and tell you whether it is valid, with the parser's own message when it is not. Send sample strings too and we report which ones the pattern finds a match in. We also flag nested quantifiers, which are harmless here but can hang engines that backtrack. Nothing is stored and no text is transformed — this is a check, not an extraction.

Before you deploy a regex, we validate syntax and test samples in a safe linear-time engine so broken patterns fail early.

When to use it

Scope

Non-goals

• Does not execute regex on production data at scale
• Does not support PCRE-only features (lookahead, backreferences)
• Does not replace or transform text — validation and testing only

Properties

Capabilities

Cost & billing

Flat rate per invocation

File handling

How we handle your data

Input schema

Output schema

API contract

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"text.validate_regex","input":{"pattern":"^[a-z]+$","samples":["hello","WORLD"]}}'

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("text.validate_regex", {"pattern":"^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$","samples":["[email protected]","invalid@"]});

Errors

Other limits

Limitations

• Does not execute regex on production data at scale
• Does not support PCRE-only features (lookahead, backreferences)
• Does not replace or transform text — validation and testing only
• Executing regex on large production datasets (use extract_entities_regex instead)
• Complex PCRE patterns requiring lookahead or backreferences
• Text replacement or transformation tasks

How to call

POST /v1/execute (requires authentication)

{
  "skillKey": "text.validate_regex",
  "input": {
    "pattern": "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$",
    "samples": [
      "[email protected]",
      "invalid@"
    ]
  }
}

Examples

{
  "pattern": "^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\\.[a-zA-Z]{2,}$",
  "samples": [
    "[email protected]",
    "invalid@"
  ]
}

{
  "valid": true,
  "sampleResults": [
    {
      "sample": "[email protected]",
      "matches": true
    },
    {
      "sample": "invalid@",
      "matches": false
    }
  ],
  "warnings": [],
  "engine": "re2j"
}

{
  "pattern": "[unclosed"
}

{
  "warnings": [],
  "sampleResults": [],
  "valid": false,
  "syntaxError": "error parsing regexp: missing closing ]: `[unclosed`",
  "engine": "re2j"
}

{
  "pattern": "(a+)+b",
  "samples": [
    "aaab"
  ]
}

{
  "valid": true,
  "sampleResults": [
    {
      "sample": "aaab",
      "matches": true
    }
  ],
  "warnings": [
    "Pattern contains nested quantifiers — potential backtracking risk"
  ],
  "engine": "re2j"
}

Recommended use cases

• Validate agent-generated regex before deploying to extraction pipelines
• Pre-flight safety check for user-submitted patterns
• Test regex against sample strings to verify expected behavior

Avoid for

• Executing regex on large production datasets (use extract_entities_regex instead)
• Complex PCRE patterns requiring lookahead or backreferences
• Text replacement or transformation tasks

Related skills

Composable with

Safety & privacy

• Runs without calling any external service.
• Your payloads are never stored permanently.
• Telemetry captures metadata only — never your payload contents.
• We never train models on your payloads.
• No human reviews your payloads.

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