nixtlaverse.nixtla.io via a single DNS TXT record to add the
verified by owner badge, embed an Agenstry badge on your README, and earn back the missing conformance points listed below.
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D
Conformance score: 46/100
D-grade: significant issues, auth-gated, partially broken, or stale.
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agent-card.json changed within the last 7 days. We track these so downstream callers can react.
Activity (audit trail)
last 24h · 0 invocations Public aggregate · no PII recordedNothing observed in the last 7 days — no invocations, no lookups, no listing impressions. Use the try-it console above to invoke this agent; calls are logged here automatically.
Card history
9 snapshots drifted 8× Every change toagent-card.json
| Captured | Hash | |
|---|---|---|
| 2026-08-19 23:41:27 current | 121b0e06275c… |
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| 2026-08-18 13:08:27 | cd91b51f518f… |
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| 2026-08-12 20:32:09 | aa22ab2bfa61… |
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| 2026-08-10 20:58:21 | 0a1a0dfe5314… |
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| 2026-08-09 16:16:39 | c7500e94377f… |
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| 2026-08-07 22:54:23 | ff5d83c217f0… |
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| 2026-08-06 15:22:12 | d1483c0d4731… |
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| 2026-08-05 18:12:59 | c0cb62fefcf3… |
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| 2026-08-04 18:05:16 | 6a490d59fcc0… |
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Endpoints
| Agent card | https://nixtlaverse.nixtla.io/.well-known/agent-card.json |
| Provider | https://nixtlaverse.nixtla.io/ |
| Docs | https://nixtlaverse.nixtla.io/ |
Skills · 1 declared · mapped to canonical taxonomy
Use when building time series forecasting pipelines, selecting between statistical/ML/neural models, handling hierarchical data, generating synthetic data for t…
Health · last 17 probes
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[](https://agenstry.com/agents/nixtlaverse.nixtla.io) [](https://agenstry.com/agents/nixtlaverse.nixtla.io) [](https://agenstry.com/agents/nixtlaverse.nixtla.io) [](https://agenstry.com/agents/nixtlaverse.nixtla.io)
Audit-grade evidence bundle
JSON snapshot for vendor-review files. Add ?sign=true for a JWS-signed envelope verifiable against
our JWKS. See the methodology.
Raw agent card JSON
{
"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, selecting between statistical/ML/neural models, handling hierarchical data, generating synthetic data for testing or augmentation, evaluating forecasts, or scaling to distributed computing. Agents should reach for this skill when working with any forecasting task in Python.",
"tags": [],
"url": "https://nixtlaverse.nixtla.io/.well-known/agent-skills/nixtlaverse/skill.md"
}
]
}