Content
80%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is a concise, highly actionable workflow with complete, runnable code and useful conventions/failure-mode tables. Its gaps are the lack of explicit validation checkpoints around the batch deletion analyses and the absence of any external reference structure despite a substantial body.
Suggestions
Add explicit validation/feedback steps for the batch operations — e.g. after single_gene_deletion, check that growth_fraction values are finite and that essential_gene count is plausible before proceeding.
Split the conventions and output-file tables into a separate reference file (e.g. references/conventions.md) and link to it from the workflow, so SKILL.md stays a lean overview.
Include a short 'validate outputs' checklist tying each step to its expected output file so missing or all-zero results are caught early.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient — each step leads with executable code and minimal prose, assuming Claude's competence; only a few short framing sentences ('turns numbers into biology') and they earn their place. | 3 / 3 |
Actionability | Fully executable COBRApy code in every step with specific thresholds (5% WT lethality, n=1000 sampling), named output files, and copy-paste-ready blocks. | 3 / 3 |
Workflow Clarity | A clear 7-step sequence with failure-mode troubleshooting is present, but there are no explicit validation checkpoints or feedback loops (validate→fix→retry) for batch operations like the gene/reaction deletion sweeps, capping clarity at 2. | 2 / 3 |
Progressive Disclosure | No bundle files exist, so the single SKILL.md is a monolith with all code, conventions, and troubleshooting inline; sections are well organized but content that could be split out (e.g. a reference table) is not separated. | 2 / 3 |
Total | 10 / 12 Passed |