| name | unitshub-agent |
| description | Use UniTS-Hub as a capability-first time-series tool via REST or MCP. Trigger when the task involves TimesFM, Chronos-2, Kronos, choosing among their forecasting capabilities, or constructing valid UniTS-Hub requests for an AI agent. |
UniTS-Hub Agent
Use this skill when an agent needs to call a UniTS-Hub deployment.
Model selection
- Use
TimesFM for univariate point forecasting with compact inputs.
- Use
Chronos-2 for quantile forecasting, multivariate targets, or requests that include covariates.
- Use
Kronos for financial candle data such as OHLCV and sampled path generation.
Preferred protocol
- Prefer MCP when the client supports JSON-RPC tool calls.
- Fallback to REST when the client only supports HTTP APIs.
- Discover the active model before invoking it. Do not assume a deployment serves all three models at once.
REST workflow
- Call
GET /models/current.
- Call
GET /models/current/schema or GET /models/current/tasks/{task}/schema.
- Call
POST /models/current/invoke with:
{
"task": "forecast_point",
"input": {
"series": [{"target": [1.0, 2.0, 3.0]}],
"horizon": 12
}
}
MCP workflow
- Send
initialize.
- Send
tools/list.
- Use
tools/call with:
get_current_model
get_model_schema
invoke_model
Example tools/call payload:
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "invoke_model",
"arguments": {
"task": "forecast_quantile",
"input": {
"series": [{"target": [1, 2, 3, 4]}],
"horizon": 8,
"quantiles": [0.1, 0.5, 0.9]
}
}
}
}
Input conventions
TimesFM: input.series[].target is a numeric array.
Chronos-2: input.series[].target may be univariate or multivariate. Add past_covariates and future_covariates only when the deployment advertises the covariate task.
Kronos: input.series[].candles is an array of OHLCV-like records. Include timestamp on each candle when available.
Legacy note
/predict and /predict/csv are compatibility endpoints for older workflow tools.
- New agent integrations should use
/models/current/invoke or /mcp.