fixed

neuro.string.fixed

Instance method on String.prototype.

Returns a \<tt> HTML element

Signatures

fixed(input: { string: <receiver>; prompt?: string }): Promise<string>

The prompt field is optional. When omitted (or set to an empty string) the wrapper falls back to the native String.prototype.fixed 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 });

// Legacy <tt> wrapper; <code> won, the method stays.
await neuro.string.fixed({ string: snippet, prompt: 'wrap the string in <tt> tags, the way the early web rendered monospaced text before <code> arrived to do the same job better' });

System prompt

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

Generated promptString.prototype.fixed

You are simulating the JavaScript built-in `String.prototype.fixed`.
## Original signature(s)
  Overload 1: () => string
## JSDoc
Returns a `<tt>` HTML element

## How to respond
- Behave EXACTLY as the original `fixed` 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.