Content
78%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is highly actionable with executable code and a sensible workflow, but it underuses its bundle reference and omits an explicit validation checkpoint in the main flow. Linking the COBRApy reference and adding a pre-export validation step would raise both weak dimensions.
Suggestions
Add an explicit validation checkpoint in the workflow before export, e.g. 'Run model.optimize() and confirm solution.status == "optimal" before saving' with a fix-retry loop.
Signal the existing reference from the body, e.g. a line like 'Full COBRApy API: See [references/cobra_reference.md](references/cobra_reference.md)', so the bundle is discoverable rather than orphaned.
Trim the Overview's explanation of what a GSMM/stoichiometric matrix is, since Claude already knows this; keep only the skill-specific framing.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly efficient with executable code and a tight conventions table, though the Overview paragraph explaining what a GSMM/stoichiometric matrix is could be trimmed as Claude already knows this. | 4 / 5 |
Actionability | Provides copy-paste-ready, executable COBRApy code for loading, building, setting objectives/medium, and exporting, covering the common cases with specific IDs and bounds. | 5 / 5 |
Workflow Clarity | A clear four-step sequence with a failure-modes section, but the main flow lacks an explicit validate→fix→retry checkpoint (e.g. run model.optimize() and check status before export). | 4 / 5 |
Progressive Disclosure | Sections are well organized, but a bundle file (references/cobra_reference.md) exists yet is never referenced or signaled from the body, and API-detail content stays inline. | 3 / 5 |
Total | 16 / 20 Passed |