Two Truths and a Lie Prompt Generator
Bounded offline two-truths-and-a-lie setup prompts,no claim of truthdetection. 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
Two-truths-and-a-lie prompts help participants prepare a set of statements for a guessing game.
Two-truths-and-a-lie prompts help participants prepare a set of statements for a guessing game.1
The tool provides setup ideas without detecting truth or evaluating the statements.
When to use Two Truths and a Lie Prompt Generator
Use this tool to draw reproducible entries from the documented fixed inventory.
How to use Two Truths and a Lie 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 | Share two real hobbies and one invented hobby |
| 1 | Share two places visited and one invented trip |
| 2 | Share two favorite foods and one invented dish |
| 3 | Share two learned skills and one fictional skill |
| 4 | Share two books read and one invented title |
| 5 | Share two real collections and one imagined collection |
| 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": [
"Share two real hobbies and one invented hobby",
"Share two learned skills and one fictional skill"
],
"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 Truth or Dare Prompt Generator. Truth-or-dare cards can offer light conversation and creative actions under agreed participation rules.
For a related operation, use Never Have I Ever Prompt Generator. Never-have-I-ever prompts offer conversation starters about everyday experiences.
References
-
Two Truths and a Lie Prompt Generator — tool.io
-
Existing seeded random generator — tool.io
Similar or alternative tools
- Truth or Dare Prompt Generator
Truth-or-dare cards can offer light conversation and creative actions under agreed participation rules.
- Never Have I Ever Prompt Generator
Never-have-I-ever prompts offer conversation starters about everyday experiences.