Content
86%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.
A tight, well-structured skill body that gives concrete paths, formulas, and a report template while assuming Claude's competence. Its only real gap is the absence of an executable example script for a skill whose core instruction is to write one.
Suggestions
Add a short copy-paste Python skeleton (load the three CSVs with pandas, compute days_cover, print the markdown sections) to close the actionability gap.
Include one lightweight verification step, e.g. assert the script's printed sections are non-empty or that joined SKU counts match, to add a validation checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient with no padding or explanation of concepts Claude already knows; every section (template, cadence table, aging-PO rule, data sources, code-note) earns its place and assumes Claude's competence. | 5 / 5 |
Actionability | Concrete guidance throughout — exact file paths, the days-of-cover formula, the aging comparison (elapsed > lead_time), and a full markdown template — but no copy-paste example script, leaving a minor gap for a code-execution skill. | 4 / 5 |
Workflow Clarity | Clear single-script workflow (load CSVs once, compute everything, print markdown) with an explicit anti-pattern to avoid (per-SKU tool calls); no validation checkpoint is given, but the operation is a non-destructive read-only report so the batch-validation cap is not the best fit, landing just above the midpoint. | 4 / 5 |
Progressive Disclosure | A short, single-purpose skill with no external references needed and well-organized section headers (Structure, Operating cadence, Aging-PO check, Data sources, Do this in code), matching the under-50-lines simple-skill exception for a top score. | 5 / 5 |
Total | 18 / 20 Passed |