Card snapshot

This is a frozen copy of the agent's agent-card.json as we observed it at the timestamp above. We capture a new snapshot every time the card's content hash changes. Useful for: forensic drift analysis, verifying downstream callers see the right version, reproducing routing decisions made historically.

{
  "name": "Nixtla",
  "url": "https://nixtlaverse.nixtla.io/",
  "version": "1.0.0",
  "protocolVersion": "0.3",
  "preferredTransport": "HTTP+JSON",
  "supportedInterfaces": [
    {
      "url": "https://nixtlaverse.nixtla.io/",
      "protocolBinding": "HTTP+JSON",
      "protocolVersion": "0.3"
    }
  ],
  "provider": {
    "url": "https://nixtlaverse.nixtla.io/",
    "organization": "Nixtla"
  },
  "documentationUrl": "https://nixtlaverse.nixtla.io/",
  "capabilities": {
    "streaming": false,
    "pushNotifications": false
  },
  "defaultInputModes": [
    "text/plain"
  ],
  "defaultOutputModes": [
    "text/plain"
  ],
  "skills": [
    {
      "id": "nixtlaverse",
      "name": "Nixtlaverse",
      "description": "Use when building time series forecasting pipelines. Reach for this skill when you need to forecast multiple time series, evaluate models, handle hierarchical data, generate synthetic data for testing, or scale forecasting to distributed clusters. The Nixtlaverse is a collection of specialized libraries for different forecasting approaches: StatsForecast for statistical models, MLForecast for machine learning, NeuralForecast for deep learning, HierarchicalForecast for coherent hierarchical predictions, and supporting utilities.",
      "tags": [],
      "url": "https://nixtlaverse.nixtla.io/.well-known/agent-skills/nixtlaverse/skill.md"
    }
  ]
}