Nanosensor Calibration Manager

SkillDev tools

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

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Nanosensor Calibration Manager skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/science/nanotechnology/skills/nanosensor-calibration-manager/SKILL.md and read by ahel’s review.

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"
  }]
}

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: nanosensor-calibration-manager
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter