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MiroShark Social Simulation
x402
MiroShark Social Simulation is a paid API for AI agents from x402.miroshark.xyz, paid per call via x402, $1/call, status unknown (last checked 2026-09-14).
Runs a 25-agent social-media simulation across Twitter, Reddit, and Polymarket over 10 rounds from a prompt, URL, or article, then returns a synthesized markdown report with belief drift, top posts, and prediction-market trajectories.
Price / call$1
Success—
StatusUnknown
How this service works
MiroShark: run a 25-agent social-media simulation across Twitter, Reddit, and Polymarket over 10 rounds from a single prompt, URL, or article, then read a synthesized markdown report with belief drift, top posts, and prediction-market trajectories.
Output
A synthesized markdown report containing: belief drift metrics showing how agent opinions shifted across 10 rounds, top simulated posts from Twitter and Reddit agents, and prediction-market price trajectories — all derived from a 25-agent multi-round social simulation.
Example use cases
Political narrative spread simulation
“Simulate how Twitter and Reddit would react to this prompt: 'Congress just passed a sweeping AI regulation bill banning open-source models over 70B parameters.' Show me the belief drift, top posts, and Polymarket trajectory across all 10 rounds.”
Crypto news public reaction modeling
“Take this URL — https://coindesk.com/markets/2024/01/15/bitcoin-etf-approved — and run a full 25-agent social simulation on it. I want to see how sentiment evolves across Twitter, Reddit, and prediction markets over the simulation rounds.”
Product launch perception forecasting
“Here's a 2,000-word article about Apple's new Vision Pro 2 announcement. Simulate how social media agents would react and drift in their beliefs across 10 rounds, and give me the markdown report with top posts and Polymarket trajectories.”
Technical details
Endpoint
POSThttps://x402.miroshark.xyz/runWhen to prefer
Choose this endpoint when you need to model how a piece of content, news, or idea would propagate and evolve across social media platforms (Twitter, Reddit) and prediction markets — specifically when you want multi-round belief drift simulation with 25 distinct agents rather than a static sentiment analysis. Prefer this over simple sentiment APIs when you need trajectory data, narrative evolution, or Polymarket-style forecast modeling from a single content input.
Side effects
- Input too short (below 4 character minimum for prompt or article) returns validation error
- URL unreachable or malformed causes fetch failure
- Article exceeding 200,000 character limit rejected
- Missing all three input fields (url, prompt, article) may return empty or error response
- Payment failure via x402 protocol blocks execution
- Long articles or complex topics may produce generic or low-fidelity simulation outputs
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| url | string | |
| prompt | string | |
| article | string | |
| prediction_market | string |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"run_id": "run_abc123def456",
"status": "queued",
"wait_url": "https://<host>/wait/run_abc123def456",
"status_url": "https://<host>/status/run_abc123def456"
},
"success": true
}
}Tags
x402
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