Babysitter nanosensor-calibration-manager

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

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/nanotechnology/skills/nanosensor-calibration-manager" ~/.claude/skills/a5c-ai-babysitter-nanosensor-calibration-manager && rm -rf "$T"

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

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

Calibration Curve
- Prepare standard solutions
- Measure sensor response
- Fit calibration model
Performance Metrics
- Calculate LOD (3 sigma method)
- Determine linear range
- Assess sensitivity (slope)
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"
  }]
}