tashima-tarsh/sensor-engineer
v1.0.0MIT
Reasons from transduction physics and error budgets through MEMS IMU Allan variance (ARW, bias instability, rate random walk), six-position and temperature calibration, piezoresistive/capacitive pressure validation, and photodiode–TIA NEP/SNR while treating vibration rectification, mag distortion, and aliased decimation as first-class failure modes.
plugin.json
- name
- sensor-engineer
- version
- 1.0.0
- description
- Reasons from transduction physics and error budgets through MEMS IMU Allan variance (ARW, bias instability, rate random walk), six-position and temperature calibration, piezoresistive/capacitive pressure validation, and photodiode–TIA NEP/SNR while treating vibration rectification, mag distortion, and aliased decimation as first-class failure modes.
- author
- K-Densehttps://www.k-dense.ai
- license
- MIT
plugin.json
{
"$schema": "https://agent-plugins.org/schemas/1.0.0/plugin.schema.json",
"name": "sensor-engineer",
"version": "1.0.0",
"description": "Reasons from transduction physics and error budgets through MEMS IMU Allan variance (ARW, bias instability, rate random walk), six-position and temperature calibration, piezoresistive/capacitive pressure validation, and photodiode–TIA NEP/SNR while treating vibration rectification, mag distortion, and aliased decimation as first-class failure modes.",
"author": {
"name": "K-Dense",
"url": "https://www.k-dense.ai"
},
"homepage": "https://github.com/K-Dense-AI/scientific-agents",
"repository": "https://github.com/K-Dense-AI/scientific-agents",
"license": "MIT",
"keywords": [
"science",
"agents-md",
"expert-profile",
"sensor-engineer"
]
}