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sensor-calibration-workbench

sensor-calibration-workbench

github.com/wedsamuel1230Other28118 installsUpdated 2w ago
Repository

About sensor-calibration-workbench

A skill for Arduino projects where sensor readings are unreliable despite the sensor working. It guides calibration, evidence collection, coefficient persistence, and revalidation.

Key features

  1. 01Choose calibration type and workflow
  2. 02Collect reference and environmental evidence
  3. 03Review warm-up, drift, and saturation issues
  4. 04Plan coefficient storage and revalidation

Use cases

  1. 01Tune a load-cell factor
  2. 02Calibrate CO2, magnetometer, or color sensors
  3. 03Store calibration coefficients in EEPROM or flash

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/wedsamuel1230/embedded-engineering-skills --skill sensor-calibration-workbench

After installing, type/sensor-calibration-workbenchin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
calibration-flow.md
common-failure-patterns.md
persistence-and-revalidation.md

Details

From the project README

Sensor Calibration Workbench

Use this skill when the sensor technically works, but the readings are not yet trustworthy enough for the project.

Resources

  • references/calibration-flow.md - end-to-end calibration workflow and evidence checklist
  • references/common-failure-patterns.md - warm-up, scaling, drift, saturation, and environment mistakes
  • references/persistence-and-revalidation.md - storing coefficients and deciding when recalibration is needed

When to Use

Use this skill when the request involves:

  • volatile or implausible sensor readings
  • "how do I calibrate this sensor?"
  • load-cell factor tuning
  • CO2, magnetometer, or color-sensor calibration
  • storing calibration coefficients in EEPROM or flash
  • deciding whether the problem is calibration, hardware, or environment

Do not use this skill when the sensor is not detected at all. That should route through hardware or bus bring-up first.

Workflow

  1. Confirm the measurement problem:
    • unstable -> open references/common-failure-patterns.md
    • offset or scaling error -> open references/calibration-flow.md
    • values good once but bad later -> open references/persistence-and-revalidation.md
  2. Identify the calibration class:
    • one-point or zero-offset
    • two-point scale calibration
    • multi-orientation or environmental calibration
  3. Collect reference evidence before changing coefficients:
    • known reference values
    • warm-up state
    • ambient conditions
    • sample stability
  4. Decide how calibration values will persist and how revalidation will be triggered after reboot, firmware update, or field drift.

Core Rules

  • Calibration without a known reference is guesswork.
  • Warm-up and stabilization time are part of calibration, not a side note.
  • Do not mix hardware-fault symptoms with coefficient-tuning symptoms.
  • Store both the calibration values and enough metadata to know when they became stale.

Verification

  • Confirm readings converge toward a known reference after calibration.
  • Confirm the calibrated values stay stable across repeated samples.
  • Confirm stored coefficients reload correctly after restart.
  • If the project has operating thresholds, verify those thresholds against the calibrated output rather than the raw sensor value.

Integration

  • Pair with i2c-bringup-diagnostician or circuit-debugger when the sensor is not yet electrically trustworthy.
  • Pair with arduino-code-generator when the user needs persistence or filtering code added to the sketch.
  • Pair with field-power-and-connectivity-triager when sensor behavior changes only off USB or under field power conditions.

Shared Output Contract

Use the shared Arduino skill contract: state assumptions, required tools and versions, implementation steps, tests/evidence by proof stage, known limitations, and recovery/security notes.

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