Deterministic scenario stream generator for AI trading agent stress-testing
Deterministic scenario stream generator for AI trading agent stress-testing. Simulates chronological event ticks (hype cycle, FUD cascade, etc.) with progressive step values.
Answeringour last check, 2026-09-24
1 of 1checks answered this week
219 msmedian answer time
$0.01listed price per call
$0.01price it asked us
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
GET https://vibesprings.net/api/mock/social/stream
| Category | Everything else |
|---|---|
| Provider host | vibesprings.net |
| Networks | eip155:8453 |
| Payment schemes | exact |
| Self-reported calls, 30 days | 1 from 1 payers (the provider's figure, not ours) |
Our checks, last 30 days
| Day | Result | HTTP | Asked | Time |
|---|---|---|---|---|
| 2026-09-24 | valid payment request | 402 | $0.01 | 219 ms |
Example input (from the provider)
{
"method": "GET",
"queryParams": {
"scenario": "hype_cycle",
"seed": "test-run-1",
"step": 5
},
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"method": {
"enum": [
"GET"
],
"type": "string"
},
"queryParams": {
"properties": {
"format": {
"description": "Output format (json, text)",
"type": "string"
},
"scenario": {
"description": "Target scenario (hype_cycle, fud_cascade, regulatory_crackdown, quiet_accumulation)",
"type": "string"
},
"seed": {
"description": "Deterministic LCG seed value",
"type": "string"
},
"step": {
"description": "Scenario chronological step index (0-10)",
"type": "integer"
}
},
"required": [],
"type": "object"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}