Cobrapy

If you're working with genome-scale metabolic models, this gives Claude the ability to run flux balance analysis, perform gene knockout simulations, and compute production envelopes using COBRApy. It's the standard Python library for constraint-based modeling in systems biology, so you can load SBML models, optimize for growth or production, run variability analysis to find flux ranges, and do knockout screens to identify essential genes. The skill covers everything from basic FBA to more advanced techniques like flux sampling and gapfilling. Useful if you're doing metabolic engineering, trying to predict what happens when you delete genes, or figuring out minimal media requirements for an organism.

skills.sh installs: 238
GitHub stars: 33.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add davila7/claude-code-templates --skill cobrapy --agent claude-code

Installs into .claude/skills of the current project.

Files

COBRApy - Constraint-Based Reconstruction and Analysis

Overview

COBRApy is a Python library for constraint-based reconstruction and analysis (COBRA) of metabolic models, essential for systems biology research. Work with genome-scale metabolic models, perform computational simulations of cellular metabolism, conduct metabolic engineering analyses, and predict phenotypic behaviors.

Core Capabilities

COBRApy provides comprehensive tools organized into several key areas:

1. Model Management

Load existing models from repositories or files:

from cobra.io import load_model

# Load bundled test models
model = load_model("textbook")  # E. coli core model
model = load_model("ecoli")     # Full E. coli model
model = load_model("salmonella")

# Load from files
from cobra.io import read_sbml_model, load_json_model, load_yaml_model
model = read_sbml_model("path/to/model.xml")
model = load_json_model("path/to/model.json")
model = load_yaml_model("path/to/model.yml")

SKILL.md on GitHub