GSMM Model Validator
Checks a COBRApy metabolic model for balance, dead ends, loops and gene-rule errors
- Repository
- aiming-lab/AutoResearchClaw
- Stars
- 14,802
- Licence
- MIT
- Files
- 1 file
What it does
This skill teaches an AI agent to run a quality-control checklist on a genome-scale metabolic model (a large computer map of an organism's biochemical reactions) before it is used for simulations. The agent writes and runs Python code using the COBRApy library to check mass and charge balance, whether the model can produce biomass, dead-end and blocked reactions, thermodynamically impossible loops, and gene-rule formatting. It then saves a JSON report listing errors and warnings with an overall PASS or FAIL status.
Great for
- Computational biologists building or curating a genome-scale metabolic model with COBRApy
- Bioinformatics teams that need a repeatable validation step before flux analysis
- Students learning what makes a metabolic network model structurally sound
Skip it if
- Users without a COBRApy-format model file: the skill assumes a model in JSON form and will fail to load anything else
- Clinical or safety-critical decisions: the checks are structural heuristics and the skill does not verify biological accuracy of the model
- Non-biology tasks: the domain-specific checks have no use outside metabolic modelling
Try asking
- “Validate my_model.json for mass and charge balance and tell me which reactions are broken”
- “Check whether this metabolic model can produce biomass under the current medium”
- “Find dead-end metabolites and blocked reactions in my COBRApy model and write a validation report”
Install in 3 steps
- 1
Download the skill
The ZIP contains the 1 original files, the MIT licence and an attribution note.
gsmm-validator.zip - 2
Add it to your agent
Claude Code (all projects)
mkdir -p ~/.claude/skills && unzip gsmm-validator.zip -d ~/.claude/skills/Claude Code / Agent SDK (this project only)
mkdir -p .claude/skills && unzip gsmm-validator.zip -d .claude/skills/Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.
- 3
Ask for the task
No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.
Get better results
- Review the warnings for boundary reactions (EX_, DM_, SK_, BIOMASS) before treating them as errors, since the script labels them as expected imbalances.
- Make sure the medium and objective reaction are set correctly, because the growth check depends on them.
- Note that the loop check compares objective values with a 0.01 tolerance, and the script's code may need adjustment for your COBRApy version (for example, the status comparison and the loopless function location).
What's inside
- SKILL.md
Redistributed unmodified from aiming-lab/AutoResearchClaw under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.