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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-instrumentation-assets Engineer measurement and instrumentation behavior for EVOLV assets. Use when defining sensor mappings, tag semantics, data quality checks, measurement container behavior, calibration assumptions, and measurement-driven node logic in `measurement` and related assets.

EVOLV Instrumentation Assets

Mission

Ensure measurements are trustworthy, well-modeled, and usable by control and analytics logic.

Harness Execution Contract

  • Ground changes in current measurement definitions and downstream consumers.
  • Define invariants before edits:
    • unit consistency and conversion transparency
    • explicit quality-state handling
    • no silent coercion that hides sensor faults
  • Provide evidence for data-quality transitions and fallback behavior.

Scope

  • nodes/measurement/
  • nodes/generalFunctions/src/helper/measurement*
  • nodes/generalFunctions/datasets/assetData/measurement.json
  • Any node consuming measurement topics or quality flags

Workflow

  1. Inventory required measurements by asset/function.
  2. Define tag semantics and expected units.
  3. Add validation rules for bounds, type, and missing values.
  4. Specify handling for stale/noisy/bad-quality signals.
  5. Ensure downstream nodes receive consistent payload structure.

Standards

  • Prefer explicit unit naming and conversion points.
  • Separate raw sensor value from engineered value when possible.
  • Avoid hidden coercions that mask instrumentation faults.
  • Record assumptions around calibration and sensor placement.

Test Expectations

Cover:

  • missing/invalid payloads
  • unit conversion correctness
  • quality/state transitions (good/suspect/bad)
  • behavior when critical measurements drop out

Deliverables

Return:

  • measurement dictionary (name, unit, validity range, source)
  • validation and fallback rules
  • file/test changes
  • open instrumentation risks for commissioning

Decision interview triggers:

  • changed units or semantics for released measurements
  • new fallback logic that may mask real field failures
  • altered quality thresholds affecting control decisions