Agent Skills: Nanosensor Calibration Manager

Nanosensor characterization skill for calibration, sensitivity analysis, and selectivity validation

applicationsID: a5c-ai/babysitter/nanosensor-calibration-manager

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/library/specializations/domains/science/nanotechnology/skills/nanosensor-calibration-manager

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library/specializations/domains/science/nanotechnology/skills/nanosensor-calibration-manager/SKILL.md

Skill Metadata

Name
nanosensor-calibration-manager
Description
Nanosensor characterization skill for calibration, sensitivity analysis, and selectivity validation

Nanosensor Calibration Manager

Purpose

The Nanosensor Calibration Manager skill provides comprehensive characterization of nanomaterial-based sensors, enabling systematic calibration, sensitivity optimization, and selectivity validation for analytical applications.

Capabilities

  • Calibration curve generation
  • Limit of detection (LOD) calculation
  • Sensitivity and dynamic range analysis
  • Selectivity and interference testing
  • Response time characterization
  • Long-term stability assessment

Usage Guidelines

Sensor Calibration

  1. Calibration Curve

    • Prepare standard solutions
    • Measure sensor response
    • Fit calibration model
  2. Performance Metrics

    • Calculate LOD (3 sigma method)
    • Determine linear range
    • Assess sensitivity (slope)
  3. Selectivity Testing

    • Test interferents
    • Calculate selectivity coefficients
    • Validate in complex matrices

Process Integration

  • Nanosensor Development and Validation Pipeline

Input Schema

{
  "sensor_id": "string",
  "analyte": "string",
  "concentration_range": {"min": "number", "max": "number", "unit": "string"},
  "interferents": ["string"],
  "matrix": "buffer|serum|environmental"
}

Output Schema

{
  "calibration": {
    "equation": "string",
    "r_squared": "number",
    "linear_range": {"min": "number", "max": "number"}
  },
  "performance": {
    "lod": "number",
    "loq": "number",
    "sensitivity": "number",
    "response_time": "number (seconds)"
  },
  "selectivity": [{
    "interferent": "string",
    "selectivity_coefficient": "number"
  }]
}