Babysitter kinetic-modeler

Reaction kinetics modeling skill for parameter estimation, mechanism validation, and rate equation development

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 "$T/library/specializations/domains/science/chemical-engineering/skills/kinetic-modeler" ~/.claude/skills/a5c-ai-babysitter-kinetic-modeler && rm -rf "$T"

manifest: library/specializations/domains/science/chemical-engineering/skills/kinetic-modeler/SKILL.md

Kinetic Modeler Skill

Purpose

The Kinetic Modeler Skill develops and validates reaction kinetics models, performing parameter estimation from experimental data and supporting reactor design.

Capabilities

Rate equation formulation (power law, LHHW, Eley-Rideal)
Parameter estimation via nonlinear regression
Arrhenius parameter calculation
Activation energy determination
Model discrimination (AIC, BIC criteria)
Confidence interval estimation
Reaction mechanism validation
Kinetic data analysis

Usage Guidelines

When to Use

Developing kinetic models
Estimating rate parameters
Validating reaction mechanisms
Supporting reactor design

Prerequisites

Experimental data available
Proposed mechanism identified
Operating conditions characterized
Thermodynamic constraints known

Best Practices

Use statistically valid data
Test multiple model forms
Validate with independent data
Report parameter uncertainties

Process Integration

This skill integrates with:

Kinetic Model Development
Reactor Design and Selection
Catalyst Evaluation and Optimization

Configuration

kinetic-modeler:
  model-types:
    - power-law
    - langmuir-hinshelwood
    - eley-rideal
    - mechanistic
  estimation-methods:
    - least-squares
    - maximum-likelihood
    - bayesian

Output Artifacts

Kinetic models
Parameter estimates
Confidence intervals
Model validation reports
Mechanism analysis