SuperAPI AI Directory

umodel-query

Agents & models

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Updated 10-15 16:47

About this skill

UModel Query — read entities, relationships, the model, and telemetry

UModel is an object-graph semantic layer: enterprise objects (services, Pods, deployments, config changes, promotions, …), their typed relationships (calls, depends_on, affects, …), and the datasets (metrics, logs) hanging off them — all read through one SPL surface via the umctl CLI (MCP alternative at the bottom).

This file is the overview + setup. Each query surface has a focused guide under references/ — read the one your task needs (don't load them all).

Setup (CLI-first)

1. Ensure umctl is on PATH — UModel's read CLI:

command -v umctl || go install github.com/alibaba/UnifiedModel/cmd/umctl@latest   # needs Go 1.22+

No Go toolchain? Download a prebuilt umctl from the repo's Releases, or build from a clone (make build-cli → ./bin/umctl). Verify with umctl version.

2. Point umctl at your UModel server — set the address explicitly (flag, env, or a saved profile):

umctl --addr http://<host>:8080 query run <workspace> "<SPL>" -o json   # per call
export UMCTL_ADDR=http://<host>:8080                                    # or for the session
umctl configure                                                         # or save a profile

3. Pick the workspace — every read takes a workspace name. List what the server has and use the one your data lives in (the bundled demo is demo):

umctl workspace list -o json

No server yet? The bundled demo serves one with sample data on :8080: make quickstart QUICKSTART_SAMPLE=examples/incident-investigation (needs a repo clone + Go).

Always pass -o json. Plain reads put column names in data.header and rows in data.data (a matrix) — zip them to read records. (Entity-call results wrap differently; see the entity-set guide.)

Query surfaces — open the reference you need

Your goal SPL surface Guide
Read objects (services, deployments, config changes…) by type / search / id .entity references/entity.md
Traverse relationships, dependencies, topology .topo references/topology.md
List what object types / datasets / links / runbooks exist .umodel references/model.md
Call an EntitySet's methods (discover via __list_method__, list datasets or Skills) .entity_set | entity-call references/entity-set.md
Read a service's metrics / logs (fetch a plan, then run it) get_metrics / get_logs references/metrics-logs.md

How they relate: .umodel defines the types. The domain + name you pass everywhere names one of those definitions — for .entity / .entity_set it's an EntitySet (.umodel with(kind='entity_set')); for get_metrics / get_logs it's a MetricSet / LogSet. .entity reads the runtime instances of an EntitySet; .entity_set calls methods on the EntitySet itself; the same domain/name join them.

Typical flow: .umodel to learn the types → .entity to find an object and grab its __entity_id__ → .topo / .entity_set / telemetry build on that id.

Notes

  • Stay read-only.
  • .entity / .topo / .umodel reads return real rows in open source. get_metrics / get_logs return an executable plan you run against Prometheus / Elasticsearch (or, against a PaaS endpoint with mode='data', rows directly) — see references/metrics-logs.md.
  • MCP alternative (instead of the CLI): connect umodel-mcp and call the query_spl_execute tool with { "workspace": "demo", "query": "<the same SPL>" } (arg key is query, not spl). Same SPL, same results.