Card snapshot
nixtlaverse.nixtla.io
·
2026-08-18 13:08:27 UTC
·
cd91b51f518fdf607594596ff805acbff964f2ccdb7e423a80b665d5ddf736e6
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 working with StatsForecast (statistical models), MLForecast (machine learning), NeuralForecast (deep learning), HierarchicalForecast (hierarchical reconciliation), SynForecast (synthetic data generation), or UtilsForecast (evaluation and utilities). Use for tasks like fitting forecasting models, generating predictions, cross-validating, reconciling hierarchical forecasts, augmenting data, and evaluating model performance.",
"tags": [],
"url": "https://nixtlaverse.nixtla.io/.well-known/agent-skills/nixtlaverse/skill.md"
}
]
}