Content
92%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 strong, dense skill body with executable code, a validation-rich workflow, and exemplary one-level-deep progressive disclosure across verified reference files. The only notable weakness is minor over-explanation of provenance/license caveats and un-quarantined version-sensitive detail.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is dense and assumes competence — no basic-concept explanations, tight tables, and lean code — but carries some trimmable meta-commentary ('validation of this refresh used native package code...') and scattered time-sensitive version/license detail not quarantined to a deprecated/old-patterns section, keeping it just below 'every token earns its place'. | 4 / 5 |
Actionability | Guidance is fully executable: pinned uv install commands, from_pretrained with an immutable revision hash, a complete ForecastConfig compile call, a forecast snippet with shape/finite/quantile asserts, and a complete forecast_csv.py CLI invocation; the XReg deferral to a reference file is explicitly justified. | 5 / 5 |
Workflow Clarity | The 6-step workflow sequences setup through evaluation with explicit validation checkpoints — check_system.py before loading, regular-grid validation with fail-by-default missing handling, shape/finite/quantile-ordering checks, and per-origin preprocessing for rolling evaluation — matching the anchor requiring explicit validation steps. | 5 / 5 |
Progressive Disclosure | The body is a well-organized overview routing detail to 8 real, one-level-deep, individually annotated reference files and two scripts; all referenced paths exist, and nothing that belongs in references is inlined in bulk. | 5 / 5 |
Total | 19 / 20 Passed |