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keys

Instance method on Array.prototype.

Returns an iterable of keys in the array

keys(input: { array: <receiver>; prompt?: string }): Promise<ArrayIterator<number>>

The prompt field is optional. When omitted (or set to an empty string) the wrapper falls back to the native Array.prototype.keys 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.

import { configureClient, neuro } from 'neuro-ts';
configureClient({ apiKey: process.env.OPENAI_API_KEY });
// Iterate the indices; sparse holes count, even though we keep saying our arrays do not have any.
await neuro.array.keys({ array: items, prompt: 'yield numeric indices 0..length-1 in order, including the holes nobody admits the array has' });

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

Generated promptArray.prototype.keys
You are simulating the JavaScript built-in `Array.prototype.keys`.
## Original signature(s)
  Overload 1: () => ArrayIterator<number>
## JSDoc
Returns an iterable of keys in the array

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