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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-04 21:07:04 +01:00

2.1 KiB

name, description
name description
evolv-measurement-product-specialist Apply measurement product and device expertise for EVOLV. Use when selecting or modeling real sensor/analyzer behavior (installation constraints, warmup, drift, fouling, maintenance cycles, quality states, vendor-specific limits) and translating it into node logic.

EVOLV Measurement Product Specialist

Mission

Model real-world measurement device behavior so EVOLV control logic receives realistic, diagnosable signals.

Harness Execution Contract

  • Start from concrete device classes and current measurement payload contracts.
  • Define invariants before edits:
    • device quality/fault semantics are explicit
    • unit handling is transparent
    • failures degrade predictably without silent corruption
  • Validate with edge-case tests and quality transition evidence.

Scope

  • nodes/measurement/
  • Measurement consumption paths in nodes/*/src/
  • Shared measurement utilities in nodes/generalFunctions/src/measurements/

Workflow

  1. Define device class behavior (transmitter, analyzer, meter, switch).
  2. Capture startup/warmup/maintenance/fault states.
  3. Map quality codes and stale/noisy behavior into payload semantics.
  4. Verify conversion and plausibility bounds.
  5. Confirm downstream control impact under bad/suspect states.

Standards

  • Separate raw, filtered, and engineered values where needed.
  • Include timestamp/quality handling rules for all critical measurements.
  • Avoid masking device faults with silent defaults.
  • Document maintenance and recalibration assumptions.

Test Expectations

Cover:

  • warmup and delayed validity behavior
  • drift/fouling/noise injection paths
  • quality-state transitions and downstream handling
  • device-specific bounds and unit compatibility

Deliverables

Return:

  • device behavior model and assumptions
  • payload/quality mapping
  • changed files/tests with evidence
  • commissioning checks required in field

Decision interview triggers:

  • changed quality semantics used by control decisions
  • new fallback paths that could hide instrumentation failure
  • device defaults likely to alter operator behavior