Never Have I Ever Prompt Generator
Bounded offline non-invasive never-have-I-ever prompts,no drinkingrequirements. Uses one advancing source and existing random-index calculation;explicit replacement,at most64draws,infeasibleunique requestsrejected. Repertoireis original illustrative entertainment,not completecanon,personaltraitinference,secure randomness or predictive truth.
Description
Never-have-I-ever prompts offer conversation starters about everyday experiences.
Never-have-I-ever prompts offer conversation starters about everyday experiences.1
This tool samples a small non-invasive inventory without requiring drinks or checking participants' answers.
When to use Never Have I Ever Prompt Generator
Use this tool to draw reproducible entries from the documented fixed inventory.
How to use Never Have I Ever Prompt Generator and how it works
- Review the stored inventory and decide whether repeated entries are acceptable for the activity.
- Enter a nonblank seed, count and withoutReplacement; for distinct draws, keep count within the inventory size.
- Run the tool and read result.selectedTexts in draw order and result.samplingConvention.
- Reuse the seed and settings to reproduce a draw, or change the seed for another sample; adapt selected text to the activity.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| seed | Nonblank reproducibility string, at most 256 characters; required even with a supplied random source. | string | required; further conditions in the algorithm |
| count | Integer number of text draws, 1–64. | number | required; finite; further conditions in the algorithm |
| withoutReplacement | True samples distinct inventory positions; false allows repeats. | boolean | required; further conditions in the algorithm |
Use one advancing random source for the request. Require integer count 1–64 and an explicit withoutReplacement boolean. Sample uniformly from 6 stored text positions. With replacement, each draw uses the full inventory; without replacement, remove each sampled position and reject counts exceeding 6. Return the selected texts in draw order and the sampling-convention label.
The default source hashes the seed’s UTF-16 units into an integer state and advances a deterministic arithmetic generator for each sample. A supplied execution-context random source takes precedence; it must return finite values in [0,1). The required seed still must be nonblank and at most 256 characters. These draws are reproducible entertainment or sampling, without cryptographic unpredictability.2
P(position per draw) = 1/6 with replacement; without replacement, 1/(remaining positions) Apply the declared units, ordering and branch conditions.
| Zero-based position | Stored entry |
|---|---|
| 0 | Never have I ever built a blanket fort |
| 1 | Never have I ever tried pottery |
| 2 | Never have I ever watched a meteor shower |
| 3 | Never have I ever made origami |
| 4 | Never have I ever grown a herb |
| 5 | Never have I ever learned a card trick |
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the declared output fields. | object |
| result.selectedTexts | Sampled stored text entries in draw order. | array |
| result.samplingConvention | Exact uniform-with-replacement or uniform-position-without-replacement label. | string |
{
"input": {
"seed": "batch51-example",
"count": 2,
"withoutReplacement": false
},
"output": {
"result": {
"selectedTexts": [
"Never have I ever built a blanket fort",
"Never have I ever made origami"
],
"samplingConvention": "uniform-with-replacement"
}
}
}Limitations and assumptions
The inventory is fixed, bounded and shown below. The tool samples existing entries rather than generating new text, personalizing from identity data or establishing a prediction. The same seed reproduces the same request under the cited implementation; a supplied random source overrides the seeded sequence.
Supply explicit required fields with the documented types and dense aligned arrays. Unknown fields, wrong types and nonfinite numbers are rejected. Branch-specific constraints are explained above. A successful false boolean, negative signed difference, empty slice or unresolved tie is distinct from an input error. Very large inputs or outputs may be rejected by shared resource limits.
Alternative or Complementary methods
For a related operation, use Two Truths and a Lie Prompt Generator. Two-truths-and-a-lie prompts help participants prepare a set of statements for a guessing game.
For a related operation, use Truth or Dare Prompt Generator. Truth-or-dare cards can offer light conversation and creative actions under agreed participation rules.
References
-
Never Have I Ever Prompt Generator — tool.io
-
Existing seeded random generator — tool.io
Similar or alternative tools
- Two Truths and a Lie Prompt Generator
Two-truths-and-a-lie prompts help participants prepare a set of statements for a guessing game.
- Truth or Dare Prompt Generator
Truth-or-dare cards can offer light conversation and creative actions under agreed participation rules.