Self-Reported vs. Measured

A cloud integration's child-device attributes arrive through one sendEvent path and render identically in the Current States table, yet some are sensor readings and some are model output computed from configuration a human typed once and never validated. Reading a computed value as evidence launders a guess into a fact.

Measured or computed

• Before trusting any attribute from a cloud integration, ask whether the upstream service measures it or computes it. Both look identical from Hubitat.
• A computed attribute is model output. Its inputs are hand-entered config (crop type, nozzle, slope, area), each entered once with no validation.
• Plausibility is not evidence. An identical value across many units with differing inputs is evidence the model echoes config, not the ground.
• When an app writes a derived attribute a rule might subscribe to, name it so a future reader can tell it is derived.

Detect it by timestamp

• Config echoed back freezes at the install timestamp. Live state carries a recent timestamp. Both arrive via sendEvent and render identically.
• Before trusting a cloud attribute, check whether its currentStates[<attr>].date has moved since install (skills/_reference/endpoints.md). A round value, identical across units, unchanged since install is a default, not a measurement.

Rank suspicion by observability

• The error rate tracks how hard the underlying fact is to observe, not whether a human typed it.
• Look-and-see fields (nozzle type, soil type) stay reliable even when hand-entered.
• Instrument-required fields (slope, area) do not, and their errors are directional, not random.
• The person who entered the data is itself a source. Ask which fields they measured, which they eyeballed, and which they left at the default. That ranks the whole set in one question.

Never impeach one guess with another

• Using one unverified field to argue a second is wrong produces a confident conclusion from two guesses.
• Verify a suspect config field against an independent measurement, never against a neighboring self-reported field.

Map the model empirically

• The integration publishes both the inputs and the outputs. The input→output wiring is measurable from the hub without vendor docs.
• Change exactly one field in the vendor's own app.
• POST /device/runmethod {"method":"refresh"} to force the integration's read immediately (skills/_reference/endpoints.md).
• Diff fullJson.currentStates before and after to see which outputs that field drove.
• Establish which inputs matter before correcting any. Field names do not state the wiring.
• Two units with matching inputs producing matching outputs confirms the model is deterministic and the full input set is identified.
• A mismatch means a hidden input.

Publishing gaps

• A cloud integration publishes the subset its author chose, not the subset that matters.
• Enumerate what it actually publishes against the vendor's own app before designing around it.
• The absent fields may be the consequential ones.