| name | debug |
| description | Tail a Hubitat hub's live log or event websocket, filtered, and interpret it against the code to diagnose an app or driver. Use when the user wants to debug, watch logs, tail the log stream, see live events, or figure out why a Hubitat app/driver misbehaves. |
Debug Skill
Process steps in order. Do not skip ahead.
Hubitat has no debugger — diagnosis is log.debug plus the live stream (logging-conventions rule). This skill tails that stream and reads it against the source.
Step 1 — Frame the question
Read skills/_reference/endpoints.md before probing for any endpoint.
Establish what is wrong and which app/driver it concerns, and pick the socket:
logsocket — the debug/info/warn/error log lines (default; use for "my code does X wrong").eventsocket — device attribute events (use for "the attribute isn't updating / the event isn't firing").
For a failure that already happened, reach for history instead of a live tail:
/device/eventsJson/<id> — when an attribute actually moved, and which app issued a command./hub/eventsJson — whether a platform update landed near the onset.
Have the source in hand so the log can be read against it. Proceed to Step 2.
Step 2 — Tail, filtered
python3 .tessl/plugins/jbaruch/hubitat-dev/skills/_scripts/hub_logtail.py --ip <addr> \
[--socket logsocket|eventsocket] [--name "<name>"] [--min-level debug] [--seconds N | --follow]
Argument and output contract, filter semantics, and frame shape: skills/_scripts/hub_logtail.py module docstring, and skills/_reference/endpoints.md for the raw frame fields. Filter tightly — --name to the app/driver under test — so the stream is readable. Default is a bounded window; use --follow only when the user will actively trigger the behavior.
Proceed to Step 3.
Step 3 — Trigger the behavior
While tailing, have the behavior exercised (press the device command, fire the app trigger, wait for the schedule). If the code lacks a log line at the point of doubt, add a guarded log.debug there (if (logEnable) log.debug "..."), redeploy with Skill(skill: "deploy"), and tail again. Proceed to Step 4.
Step 4 — Read the frames against the source
A missing expected line means the branch wasn't reached; a groovy.lang.MissingMethodException or null error names the failing call. Cross-reference the groovy-gotchas and lifecycle rules — a handler that never logs is often the string-name, the first-run-installed(), or the 2.5.1 e.statusCode trap, where the NPE escapes the catch and kills the recovery below it.
A status is not a fact. Read lastPollDate, authTokenExpires, or an event date; treat a status label as cached state, never a probe. Verify an action by re-reading what it changed (/device/fullJson/<id>, /device/eventsJson/<id>), never by the app's own "I did X" line.
A value's timestamp is not a liveness signal. A frozen attribute's event date dates the last change, not the last report — a steady world and a dead integration look identical. Read liveness off a monotonic attribute (thermostatTime) or your own stamped read, never off a value's timestamp or an attribute merely named like one (lastPoll). Full split: rules/state-vs-attributes.md. Radios: rules/zwave-zigbee-mesh.md. Endpoint timezone and ordering splits: skills/_reference/endpoints.md.
Reconcile disagreeing sources before diagnosing. Proceed to Step 5.
Step 5 — Report
State the diagnosis with the evidence (the frame that showed it) and the fix. Separate proven from inferred — name which claims a frame or a timestamp demonstrates, and which are correlation you have not bisected. If the fix is a code change, offer to apply it and redeploy. Finish here.
