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Skills cobrapy
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cobrapy
Content revision r1 Safe ⚡ Contains scripts⚙️ External commands🌐 Network access
Analyze Metabolic Models with COBRApy
Systems biology teams need reliable guidance for COBRApy analyses, from model loading to flux studies. This skill provides focused workflows and API patterns for Claude, Codex, and Claude Code.
Supports: Claude Codex Code(CC)
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "cobrapy" from https://skillstore.io/skills/k-dense-ai-cobrapy.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-cobrapy/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "cobrapy". I need to find essential genes in an E. coli model.
Expected outcome:
A structured workflow for loading the model, running baseline growth, applying single gene deletion, filtering growth results, and interpreting essentiality.
Using "cobrapy". My model is feasible, but several fluxes have wide ranges.
Expected outcome:
A diagnostic plan using FVA, loopless FVA, flux sampling, and reaction-specific plots to explain uncertainty and alternate pathways.
Using "cobrapy". I want to improve acetate production while preserving growth.
Expected outcome:
A production analysis plan covering target objective setup, minimum growth constraints, production envelopes, candidate knockouts, and result interpretation.
Security Audit
Safev7 • 7/6/2026 Open versioned report
The static analyzer flagged 71 patterns, but review showed they are documentation false positives in Markdown. Python import statements, COBRApy object identifiers, code fences, and a public documentation URL do not execute commands, access secrets, or perform network activity. No semantic prompt injection or data-exfiltration intent was found.
3
Files scanned
1,713
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
⚡ Contains scripts (4)
⚙️ External commands (50)
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🌐 Network access (1)
No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.
Audited by: codex View Audit History →
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https://skillstore.io/skills/k-dense-ai-cobrapy/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<a href="https://skillstore.io/skills/k-dense-ai-cobrapy?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-cobrapy/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/k-dense-ai-cobrapy.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). cobrapy security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-cobrapy/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-cobrapy-2026,
author = {K-Dense-AI},
title = {cobrapy security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-cobrapy/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "cobrapy security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-cobrapy/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-cobrapy:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
Higher Skillstore usage
Author / source Skillstore Score Evidence Confidence Skillstore usage Updated
k-dense-ai-cobrapy
Skillstore Score 74
Evidence Confidence High
Skillstore usage 12
Updated
2026-08-21
davila7-cobrapy
Skillstore Score 74
Evidence Confidence High
Skillstore usage 7
Updated
2026-08-21
Skillstore Score
Why this score Evidence Confidence: High 41
Architecture
85
Maintainability
87
Content
71
Community
83
Spec Compliance
What You Can Build
Run Baseline Metabolic Simulations
Load a model, check feasibility, run FBA, and interpret growth and flux outputs.
Screen Engineering Targets
Evaluate gene or reaction knockouts and compare effects on growth or product formation.
Teach COBRApy Workflows
Turn core COBRApy APIs into clear examples for model structure, constraints, and validation.
Try These Prompts
Load and Inspect a Model
Use the cobrapy skill to explain how to load the textbook model, inspect reactions, metabolites, and genes, and check growth feasibility.
Plan FBA and FVA
Use the cobrapy skill to plan flux balance analysis and flux variability analysis for my SBML model. Include validation steps and expected outputs.
Design a Knockout Screen
Use the cobrapy skill to design a gene knockout screen that identifies essential genes, neutral genes, and growth effects. Include practical thresholds.
Evaluate a Production Strategy
Use the cobrapy skill to compare production envelopes, media constraints, FVA, and knockout combinations for a target metabolite. Explain tradeoffs.
Best Practices
- Validate model feasibility before running expensive analyses or comparing biological scenarios.
- Use context managers for temporary objective, medium, bound, or knockout changes.
- Check solver status and numerical stability before interpreting growth or flux values.
Avoid
- Do not compare knockout results against an undefined or stale baseline growth value.
- Do not modify reaction bounds without recording the biological assumption behind each constraint.
- Do not treat computational predictions as experimental evidence without domain review.
Frequently Asked Questions
What is COBRApy used for?
COBRApy supports constraint-based analysis of metabolic models, including growth prediction, flux studies, knockouts, and model validation.
Can this skill analyze SBML models?
Yes. It explains how to load, save, validate, and analyze SBML models through COBRApy workflows.
Does this skill run solvers automatically?
No. It provides guidance and examples. The user environment must provide COBRApy, compatible solvers, and model files.
Can it help with gene knockout studies?
Yes. It covers single and double deletion workflows, essential gene filtering, and growth impact interpretation.
Does it support metabolic engineering tasks?
Yes. It includes production envelopes, media constraints, gapfilling, and knockout strategy guidance for target metabolites.
What should users verify before trusting results?
Users should verify model quality, solver status, objective choice, constraints, biological assumptions, and experimental relevance.
Developer Details
Author
K-Dense-AILicense
GPL-2.0 license
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/cobrapyRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
11 downloads · 241 views
File structure
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