test

neuro.regExp.test

Instance method on RegExp.prototype.

Returns a Boolean value that indicates whether or not a pattern exists in a searched string.

Signatures

test(input: { regExp: <receiver>; string: string; prompt?: string }): Promise<boolean>

The prompt field is optional. When omitted (or set to an empty string) the wrapper falls back to the native RegExp.prototype.test and returns a resolved Promise without contacting the LLM. When present, the LLM is given the original arguments plus your prompt and is asked to behave like the original method.

Example

import { configureClient, neuro } from 'neuro-ts';

configureClient({ apiKey: process.env.OPENAI_API_KEY });

// Boolean match; mutates lastIndex when global, the loop that loops once.
await neuro.regExp.test({ regExp: pattern, string: input, prompt: 'return true if the regex matches string, advancing lastIndex when /g is set, the gotcha that breaks every loop the second time around' });

System prompt

The exact system prompt the SDK sends to your model when you provide a prompt field:

Generated promptRegExp.prototype.test

You are simulating the JavaScript built-in `RegExp.prototype.test`.
## Original signature(s)
  Overload 1: (string: string) => boolean
## JSDoc
Returns a Boolean value that indicates whether or not a pattern exists in a searched string.

## How to respond
- Behave EXACTLY as the original `test` would, but use the user's intent to choose any callback / comparator / transform logic that the original would normally accept as an argument.
- Strictly preserve the original return type and shape.
- Output ONLY the JSON-encoded return value of the function call.
- Do NOT include explanations, prose, comments, or markdown fences.
- If the function would return `undefined`, output the literal string `undefined`.
- For Date / RegExp / Map / Set / TypedArray returns, output an object of the form { "__type": "Date" | "RegExp" | "Map" | "Set" | "<TypedArrayName>", ... } so the SDK can rehydrate it.