{"slug":"k-dense-ai-cobrapy","name":"cobrapy","description":"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.","long_description":"---\nname: cobrapy\ndescription: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.\nlicense: GPL-2.0 license\nallowed-tools: Read Write Edit Bash\ncompatibility: Requires Python 3.9+ (cobra 0.30+ dropped 3.8). Install with uv pip install. GLPK (swiglpk) is the default solver; CPLEX/Gurobi optional. load_model fetches from bundled data, BiGG, or BioModels (network required for remote models).\nmetadata:\n  version: \"1.1\"\n  skill-author: K-Dense Inc.\n---\n\n# COBRApy - Constraint-Based Reconstruction and Analysis\n\n## Overview\n\nCOBRApy 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.\n\n**Version note:** Examples target **cobra 0.31.1** on PyPI (import `cobra`). Docs: [cobrapy.readthedocs.io](https://cobrapy.readthedocs.io/en/latest/). Repo: [opencobra/cobrapy](https://github.com/opencobra/cobrapy).\n\n## When to Use This Skill\n\nUse this skill when:\n- Loading, building, or exporting genome-scale metabolic models (SBML, JSON, YAML)\n- Running FBA, pFBA, FVA, or flux sampling on COBRA models\n- Performing gene or reaction knockout screens and production envelope analysis\n- Designing or optimizing growth media and exchange constraints\n- Gap-filling infeasible models or validating model consistency\n\n## Installation\n\n```bash\nuv pip install \"cobra==0.31.1\"\n```\n\nMATLAB model I/O (optional):\n\n```bash\nuv pip install \"cobra[array]==0.31.1\"\n```\n\nCOBRApy uses [optlang](https://optlang.readthedocs.io/) for solvers. GLPK installs automatically via `swiglpk`. For large MILPs/QPs, cobra 0.29+ adds a **hybrid** solver (HIGHS/OSQP); `model.solver = \"osqp\"` now routes through hybrid and may error on plain LPs in a future release—prefer `model.solver = \"hybrid\"` when available.\n\n## Core Capabilities\n\nCOBRApy provides comprehensive tools organized into several key areas:\n\n### 1. Model Management\n\nLoad existing models from repositories or files:\n```python\nfrom cobra.io import load_model\n\n# Bundled locally (no network): textbook, iJO1366, salmonella\nmodel = load_model(\"textbook\")      # alias for e_coli_core (95 reactions)\nmodel = load_model(\"e_coli_core\")   # same core E. coli model\nmodel = load_model(\"iJO1366\")       # genome-scale E. coli (bundled)\nmodel = load_model(\"salmonella\")    # Salmonella iYS1720 (bundled)\n\n# Remote (BiGG / BioModels; requires network, cached after first fetch)\nmodel = load_model(\"iML1515\")       # E. coli genome-scale on BiGG\n\n# Load from files\nfrom cobra.io import read_sbml_model, load_json_model, load_yaml_model\nmodel = read_sbml_model(\"path/to/model.xml\")\nmodel = load_json_model(\"path/to/model.json\")\nmodel = load_yaml_model(\"path/to/model.yml\")\n```\n\nSave models in various formats:\n```python\nfrom cobra.io import write_sbml_model, save_json_model, save_yaml_model\nwrite_sbml_model(model, \"output.xml\")  # Preferred format\nsave_json_model(model, \"output.json\")  # For Escher compatibility\nsave_yaml_model(model, \"output.yml\")   # Human-readable\n```\n\n### 2. Model Structure and Components\n\nAccess and inspect model components:\n```python\n# Access components\nmodel.reactions      # DictList of all reactions\nmodel.metabolites    # DictList of all metabolites\nmodel.genes          # DictList of all genes\n\n# Get specific items by ID or index\nreaction = model.reactions.get_by_id(\"PFK\")\nmetabolite = model.metabolites[0]\n\n# Inspect properties\nprint(reaction.reaction)        # Stoichiometric equation\nprint(reaction.bounds)          # Flux constraints\nprint(reaction.gene_reaction_rule)  # GPR logic\nprint(metabolite.formula)       # Chemical formula\nprint(metabolite.compartment)   # Cellular location\n```\n\n### 3. Flux Balance Analysis (FBA)\n\nPerform standard FBA simulation:\n```python\n# Basic optimization\nsolution = model.optimize()\nprint(f\"Objective value: {solution.objective_value}\")\nprint(f\"Status: {solution.status}\")\n\n# Access fluxes\nprint(solution.fluxes[\"PFK\"])\nprint(solution.fluxes.head())\n\n# Fast optimization (objective value only)\nobjective_value = model.slim_optimize()\n\n# Change objective\nmodel.objective = \"ATPM\"\nsolution = model.optimize()\n```\n\nParsimonious FBA (minimize total flux):\n```python\nfrom cobra.flux_analysis import pfba\nsolution = pfba(model)\n```\n\nGeometric FBA (find central solution):\n```python\nfrom cobra.flux_analysis import geometric_fba\nsolution = geometric_fba(model)\n```\n\n### 4. Flux Variability Analysis (FVA)\n\nDetermine flux ranges for all reactions:\n```python\nfrom cobra.flux_analysis import flux_variability_analysis\n\n# Standard FVA\nfva_result = flux_variability_analysis(model)\n\n# FVA at 90% optimality\nfva_result = flux_variability_analysis(model, fraction_of_optimum=0.9)\n\n# Loopless FVA (eliminates thermodynamically infeasible loops)\nfva_result = flux_variability_analysis(model, loopless=True)\n\n# FVA for specific reactions\nfva_result = flux_variability_analysis(\n    model,\n    reaction_list=[\"PFK\", \"FBA\", \"PGI\"]\n)\n```\n\n### 5. Gene and Reaction Deletion Studies\n\nPerform knockout analyses:\n```python\nfrom cobra.flux_analysis import (\n    single_gene_deletion,\n    single_reaction_deletion,\n    double_gene_deletion,\n    double_reaction_deletion\n)\n\n# Single deletions\ngene_results = single_gene_deletion(model)\nreaction_results = single_reaction_deletion(model)\n\n# Double deletions (uses multiprocessing)\ndouble_gene_results = double_gene_deletion(\n    model,\n    processes=4  # Number of CPU cores\n)\n\n# Manual knockout using context manager\nwith model:\n    model.genes.get_by_id(\"b0008\").knock_out()\n    solution = model.optimize()\n    print(f\"Growth after knockout: {solution.objective_value}\")\n# Model automatically reverts after context exit\n```\n\n### 6. Growth Media and Minimal Media\n\nManage growth medium:\n```python\n# View current medium\nprint(model.medium)\n\n# Modify medium (must reassign entire dict)\nmedium = model.medium\nmedium[\"EX_glc__D_e\"] = 10.0  # Set glucose uptake\nmedium[\"EX_o2_e\"] = 0.0       # Anaerobic conditions\nmodel.medium = medium\n\n# Calculate minimal media\nfrom cobra.medium import minimal_medium\n\n# Minimize total import flux\nmin_medium = minimal_medium(model, minimize_components=False)\n\n# Minimize number of components (uses MILP, slower)\nmin_medium = minimal_medium(\n    model,\n    minimize_components=True,\n    open_exchanges=True\n)\n```\n\n### 7. Flux Sampling\n\nSample the feasible flux space:\n```python\nfrom cobra.sampling import sample\n\n# Sample using OptGP (default, supports parallel processing)\nsamples = sample(model, n=1000, method=\"optgp\", processes=4)\n\n# Sample using ACHR\nsamples = sample(model, n=1000, method=\"achr\")\n\n# Validate samples\nfrom cobra.sampling import OptGPSampler\nsampler = OptGPSampler(model, processes=4)\nsampler.sample(1000)\nvalidation = sampler.validate(sampler.samples)\nprint(validation.value_counts())  # Should be all 'v' for valid\n```\n\n### 8. Production Envelopes\n\nCalculate phenotype phase planes:\n```python\nfrom cobra.flux_analysis import production_envelope\n\n# Standard production envelope\nenvelope = production_envelope(\n    model,\n    reactions=[\"EX_glc__D_e\", \"EX_o2_e\"],\n    objective=\"EX_ac_e\"  # Acetate production\n)\n\n# With carbon yield\nenvelope = production_envelope(\n    model,\n    reactions=[\"EX_glc__D_e\", \"EX_o2_e\"],\n    carbon_sources=\"EX_glc__D_e\"\n)\n\n# Visualize (use matplotlib or pandas plotting)\nimport matplotlib.pyplot as plt\nenvelope.plot(x=\"EX_glc__D_e\", y=\"EX_o2_e\", kind=\"scatter\")\nplt.show()\n```\n\n### 9. Gapfilling\n\nAdd reactions to make models feasible:\n```python\nfrom cobra.flux_analysis import gapfill\n\n# Provide a universal reaction database (SBML/JSON); not bundled in cobra 0.31+\nfrom cobra.io import read_sbml_model\nuniversal = read_sbml_model(\"path/to/universal_reactions.xml\")\n\n# Perform gapfilling\nwith model:\n    # Remove reactions to create gaps for demonstration\n    model.remove_reactions([model.reactions.PGI])\n\n    # Find reactions needed\n    solution = gapfill(model, universal)\n    print(f\"Reactions to add: {solution}\")\n```\n\n### 10. Model Building\n\nBuild models from scratch:\n```python\nfrom cobra import Model, Reaction, Metabolite\n\n# Create model\nmodel = Model(\"my_model\")\n\n# Create metabolites\natp_c = Metabolite(\"atp_c\", formula=\"C10H12N5O13P3\",\n                   name=\"ATP\", compartment=\"c\")\nadp_c = Metabolite(\"adp_c\", formula=\"C10H12N5O10P2\",\n                   name=\"ADP\", compartment=\"c\")\npi_c = Metabolite(\"pi_c\", formula=\"HO4P\",\n                  name=\"Phosphate\", compartment=\"c\")\n\n# Create reaction\nreaction = Reaction(\"ATPASE\")\nreaction.name = \"ATP hydrolysis\"\nreaction.subsystem = \"Energy\"\nreaction.lower_bound = 0.0\nreaction.upper_bound = 1000.0\n\n# Add metabolites with stoichiometry\nreaction.add_metabolites({\n    atp_c: -1.0,\n    adp_c: 1.0,\n    pi_c: 1.0\n})\n\n# Add gene-reaction rule\nreaction.gene_reaction_rule = \"(gene1 and gene2) or gene3\"\n\n# Add to model\nmodel.add_reactions([reaction])\n\n# Add boundary reactions\nmodel.add_boundary(atp_c, type=\"exchange\")\nmodel.add_boundary(adp_c, type=\"demand\")\n\n# Set objective\nmodel.objective = \"ATPASE\"\n```\n\n## Common Workflows\n\n### Workflow 1: Load Model and Predict Growth\n\n```python\nfrom cobra.io import load_model\n\n# Load model (textbook = fast tutorial; iJO1366 / iML1515 for genome-scale)\nmodel = load_model(\"textbook\")\n\n# Run FBA\nsolution = model.optimize()\nprint(f\"Growth rate: {solution.objective_value:.3f} /h\")\n\n# Show active pathways\nprint(solution.fluxes[solution.fluxes.abs() > 1e-6])\n```\n\n### Workflow 2: Gene Knockout Screen\n\n```python\nfrom cobra.io import load_model\nfrom cobra.flux_analysis import single_gene_deletion\n\n# Load model\nmodel = load_model(\"textbook\")\nbaseline = model.slim_optimize()\n\n# Perform single gene deletions\nresults = single_gene_deletion(model)\n\n# Find essential genes (growth < threshold)\nessential_genes = results[results[\"growth\"] < 0.01]\nprint(f\"Found {len(essential_genes)} essential genes\")\n\n# Find genes with minimal impact\nneutral_genes = results[results[\"growth\"] > 0.9 * baseline]\n```\n\n### Workflow 3: Media Optimization\n\n```python\nfrom cobra.io import load_model\nfrom cobra.medium import minimal_medium\n\n# Load model\nmodel = load_model(\"textbook\")\n\n# Calculate minimal medium for 50% of max growth\ntarget_growth = model.slim_optimize() * 0.5\nmin_medium = minimal_medium(\n    model,\n    target_growth,\n    minimize_components=True\n)\n\nprint(f\"Minimal medium components: {len(min_medium)}\")\nprint(min_medium)\n```\n\n### Workflow 4: Flux Uncertainty Analysis\n\n```python\nfrom cobra.io import load_model\nfrom cobra.flux_analysis import flux_variability_analysis\nfrom cobra.sampling import sample\n\n# Load model\nmodel = load_model(\"textbook\")\n\n# First check flux ranges at optimality\nfva = flux_variability_analysis(model, fraction_of_optimum=1.0)\n\n# For reactions with large ranges, sample to understand distribution\nsamples = sample(model, n=1000)\n\n# Analyze specific reaction\nreaction_id = \"PFK\"\nimport matplotlib.pyplot as plt\nsamples[reaction_id].hist(bins=50)\nplt.xlabel(f\"Flux through {reaction_id}\")\nplt.ylabel(\"Frequency\")\nplt.show()\n```\n\n### Workflow 5: Context Manager for Temporary Changes\n\nUse context managers to make temporary modifications:\n```python\n# Model remains unchanged outside context\nwith model:\n    # Temporarily change objective\n    model.objective = \"ATPM\"\n\n    # Temporarily modify bounds\n    model.reactions.EX_glc__D_e.lower_bound = -5.0\n\n    # Temporarily knock out genes\n    model.genes.b0008.knock_out()\n\n    # Optimize with changes\n    solution = model.optimize()\n    print(f\"Modified growth: {solution.objective_value}\")\n\n# All changes automatically reverted\nsolution = model.optimize()\nprint(f\"Original growth: {solution.objective_value}\")\n```\n\n## Key Concepts\n\n### DictList Objects\nModels use `DictList` objects for reactions, metabolites, and genes - behaving like both lists and dictionaries:\n```pyt","tagline":"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.","category":"design-creative","tags":["agent-skill"],"author":"K-Dense-AI","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github fast track","sourceDetail":"K-Dense-AI/scientific-agent-skills","creatorName":"K-Dense-AI","creatorUrl":"https://github.com/K-Dense-AI","sourceUrl":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":41318,"forks":3810,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":55.41},"quality":{"score":92,"tier":"excellent","label":"Excellent","summary":"High-confidence pick with strong adoption and healthy maintenance signals.","signals":[{"label":"GitHub stars","value":"41K","tone":"positive"},{"label":"Freshness","value":"5d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"GPL-2.0 license","tone":"neutral"}],"warnings":[]},"trust":{"version":"trust-score-v5","score":73,"base_score":81,"outcome_confidence":0,"tier":"review","label":"Sandbox only","summary":"Useful candidate with missing or mixed trust signals. 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issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"5d since push"},{"status":"pass","label":"License clarity","detail":"GPL-2.0 license"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"warn","label":"Dependency/runtime risk","detail":"command execution surface, external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"fail","label":"Permission surface","detail":"shell or command execution, filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy"},{"status":"pass","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"1 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern","Outcome loop is ready but needs first real agent run"],"warnings":["Financial research output is not financial advice; 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require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":81,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout."}}},"trust_score_v4":{"version":"trust-score-v4","score":81,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":100,"weight":0.13,"status":"pass","detail":"41K GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":97,"weight":0.08,"status":"pass","detail":"41K stars, 3.8K forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"5d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"GPL-2.0 license"},{"id":"documentation","label":"README/SKILL.md completeness","score":86,"weight":0.14,"status":"pass","detail":"Metadata includes enough usage and workflow context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":46,"weight":0.12,"status":"warn","detail":"command execution surface, external package install surface"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":36,"weight":0.07,"status":"fail","detail":"shell or command execution, filesystem or document access"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy"},{"id":"review_status","label":"Review status","score":88,"weight":0.05,"status":"pass","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"pass","label":"GitHub adoption","detail":"41K GitHub stars"},{"status":"pass","label":"Stars/forks activity","detail":"41K stars, 3.8K forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"5d since push"},{"status":"pass","label":"License clarity","detail":"GPL-2.0 license"},{"status":"pass","label":"README/SKILL.md completeness","detail":"Metadata includes enough usage and workflow context"},{"status":"warn","label":"Dependency/runtime risk","detail":"command execution surface, external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"fail","label":"Permission surface","detail":"shell or command execution, filesystem or document access"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy"},{"status":"pass","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"pass","label":"OpenAgentSkill usage","detail":"1 views, 0 install copies"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Large GitHub adoption signal","Install command has no obvious high-risk pattern"],"warnings":["Financial research output is not financial advice; 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require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["design-creative","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace","Autonomous investment, trading, tax, or suitability decisions without a qualified human review"],"knownRisks":["Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":55,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"experimental","label":"Experimental","badge":"EXPERIMENTAL","summary":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","auto_install_policy":"review","reasons":["High-risk permission hints: Shell or command execution","55/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"needs_review","permission_hints":[{"id":"shell","label":"Shell or command execution","reason":"Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.","severity":"high"},{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"},{"id":"filesystem","label":"Filesystem access","reason":"Skill may read or write project files, documents, generated artifacts, or local workspace state.","severity":"medium"},{"id":"database","label":"Database access","reason":"Skill may inspect schemas, query databases, or work with persistent stores.","severity":"medium"}],"policy_warnings":["High-risk permission hints: Shell or command execution","Dependency or permission surface needs review"],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"experimental","label":"Experimental","badge":"EXPERIMENTAL","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","reasons":["High-risk permission hints: Shell or command execution","55/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"failed","score":79,"risk_level":"high","decision":{"recommendation":"do_not_auto_install","reason":"Permission surface: shell or command execution, filesystem or document access","auto_install_allowed":false,"policy":"block","human_review_required":true},"blockers":["Permission surface: shell or command execution, filesystem or document access"],"warnings":["Trust score: Good trust signals with a few areas worth checking before rollout.","Audit score: Needs review","Agent safety gate: Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":84,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate cobrapy before installing it in an agent workflow","design-creative","GitHub automation workflows; Claude Code teams; teams that value GitHub adoption signals"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy"]},{"id":"trust_score","label":"Trust score","status":"warn","score":81,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","41K GitHub stars","GPL-2.0 license"]},{"id":"audit_score","label":"Audit score","status":"warn","score":87,"required_for_auto_install":true,"detail":"Needs review","evidence":["Dependency or permission surface needs review"]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":55,"required_for_auto_install":true,"detail":"Sparse or mixed signals. Useful for discovery, but not for autonomous installation.","evidence":["Test manually in an isolated workspace and compare against safer alternatives.","High-risk permission hints: Shell or command execution"]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"pass","score":86,"required_for_auto_install":false,"detail":"Metadata includes enough usage and workflow context","evidence":["Strong README/SKILL.md context"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"GPL-2.0 license","evidence":["GPL-2.0 license"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"5d since push","evidence":["5d since push"]},{"id":"permission_surface","label":"Permission surface","status":"fail","score":36,"required_for_auto_install":true,"detail":"shell or command execution, filesystem or document access","evidence":["Shell or command execution: high","Network access: medium","Filesystem access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy/evals","api":"/api/agent/evals?slug=k-dense-ai-cobrapy","text":"/api/agent/evals?slug=k-dense-ai-cobrapy&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-cobrapy","name":"cobrapy","description":"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Search sources","Extract claims"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cobrapy"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cobrapy\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cobrapy\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cobrapy\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-cobrapy/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cobrapy"},"trust":{"score":81,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"41K GitHub stars","repoActivity":"41K stars, 3.8K forks","lastPushed":"5d since push","license":"GPL-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":87,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Design and creative production","scenario":"Design and creative","maintenance":"5d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No major risk signals from current metadata","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision."],"agent_contract":{"task_input":"Use cobrapy in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 81/100 Strong shortlist","Audit: 87/100 Needs review","Safety: 55/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-cobrapy (cobrapy)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-cobrapy","task":"Use cobrapy in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-cobrapy","audit":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-cobrapy&task=Use%20cobrapy%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cobrapy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cobrapy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-cobrapy/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cobrapy"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"k-dense-ai-cobrapy","name":"cobrapy","description":"Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.","category":"design-creative","url":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","github_repo":"K-Dense-AI/scientific-agent-skills"},"suited_tasks":["GitHub automation workflows","Claude Code teams","teams that value GitHub adoption signals","Inspect repository metadata","Compare code changes","Write concise engineering summaries","Search sources","Extract claims"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cobrapy"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"cobrapy\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"cobrapy\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"cobrapy\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/k-dense-ai-cobrapy/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cobrapy"},"trust":{"score":81,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"41K GitHub stars","repoActivity":"41K stars, 3.8K forks","lastPushed":"5d since push","license":"GPL-2.0 license","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","installSafety":"standard package or runtime install path","permissionSurface":"shell or command execution, filesystem or document access","documentation":"Strong README/SKILL.md context","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["design-creative","agent-skill"],"known_risks":["Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":87,"risk_level":"needs_review","risk_label":"Needs review","warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"safety_gate":{"tier":"experimental","label":"Experimental","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Test manually in an isolated workspace and compare against safer alternatives."},"quality":{"score":92,"label":"Excellent"},"supply":{"track":"Design and creative production","scenario":"Design and creative","maintenance":"5d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","high-compliance environments without internal security review","No major risk signals from current metadata","High-risk permission hints: Shell or command execution","Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision."],"agent_contract":{"task_input":"Use cobrapy in an agent workflow","recommended_action":"Test manually in an isolated workspace and compare against safer alternatives.","install_policy":"review","minimum_review_before_use":["Trust: 81/100 Strong shortlist","Audit: 87/100 Needs review","Safety: 55/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"k-dense-ai-cobrapy (cobrapy)","install_command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","risk_summary":"Needs review; Experimental; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"k-dense-ai-cobrapy","task":"Use cobrapy in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy","api":"https://www.openagentskill.com/api/agent/skills/k-dense-ai-cobrapy","audit":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=k-dense-ai-cobrapy&task=Use%20cobrapy%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%20cobrapy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%20cobrapy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/k-dense-ai-cobrapy/install","manifest":"https://www.openagentskill.com/api/registry/manifest/k-dense-ai-cobrapy"}},"supply_profile":{"track":{"slug":"design","label":"Design and creative production","shortLabel":"Design","description":"Design assets, images, video, audio, multimodal media, presentation, and creative production skills."},"scenario":{"label":"Design and creative","description":"I need my agent to produce design assets, UI directions, presentations, or creative media workflows.","useCases":[{"slug":"github-automation","title":"GitHub automation"},{"slug":"research-agents","title":"Research agents"},{"slug":"browser-automation","title":"Browser automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":41318,"starsLabel":"41K","forks":3810,"license":"GPL-2.0 license","qualityScore":92,"trustScore":81,"auditScore":87},"maintenance":{"status":"fresh","label":"5d since push","daysSincePush":5,"lastPushedAt":"2026-08-31T17:14:03+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access"]},"coverageTags":["Design","Design and creative","design-creative","agent-skill"]},"audit":{"audit_score":87,"risk_level":"needs_review","risk_label":"Needs review","quality_score":92,"trust_score":81,"maintenance_score":100,"security_score":78,"install_score":92,"warnings":["Dependency or permission surface needs review","Permission surface may require sandboxing","Financial research output is not financial advice; require human review before any live investment decision","Financial research output is not financial advice; require human review before any live investment decision.","Permission surface needs review: shell or command execution, filesystem or document access","Dependency/runtime risk: command execution surface, external package install surface","Permission surface: shell or command execution, filesystem or document access"]},"quality_signals":{"model":"v2","star_score":32.31,"usage_score":0,"review_score":5.1,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"github-automation","title":"GitHub automation","url":"https://www.openagentskill.com/use-cases/github-automation"},{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"design-creative","title":"Design and creative","url":"https://www.openagentskill.com/use-cases/design-creative"}],"stacks":[{"slug":"frontend-product-ui","title":"Frontend and UI","url":"https://www.openagentskill.com/collections/frontend-product-ui"},{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"}],"install":"npx skills add K-Dense-AI/scientific-agent-skills --skill cobrapy","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add k-dense-ai-cobrapy","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"cobrapy\" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"cobrapy\" as a Claude Code skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"cobrapy\" from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"k-dense-ai-cobrapy\",\"task\":\"Install cobrapy\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","github_repo":"K-Dense-AI/scientific-agent-skills","version":"1.0.0","license":"GPL-2.0 license","urls":{"web":"https://www.openagentskill.com/skills/k-dense-ai-cobrapy","repository":"https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/cobrapy","api":"/api/agent/skills/k-dense-ai-cobrapy","install_api":"/api/skills/k-dense-ai-cobrapy/install"},"meta":{"created_at":"2026-09-01T14:41:27.845168+00:00","updated_at":"2026-09-01T14:41:27.993148+00:00","agent_friendly":true}}