Content
31%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 a persona definition dressed as a skill: an exhaustive, well-headed catalog of data-science knowledge that Claude already has, with abstract instructions and no executable guidance, code, commands, or validation procedures. It is padded rather than instructive, and with no bundle files or references, everything is inlined into a single monolithic document.
Suggestions
Cut the Capabilities, Behavioral Traits, and Knowledge Base catalogs (or compress to a few lines of scope); Claude already knows what a data scientist does — replace them with task-specific guidance, tool choices, or decision rules it would not derive on its own.
Make the Instructions and Response Approach concrete: for common workflows (e.g. churn modeling, A/B test analysis, forecasting), give specific steps, recommended libraries/commands, and explicit validation checkpoints (e.g. "check class imbalance before choosing a metric", "run a power analysis before the experiment").
If detailed material must be kept, split it into one-level-deep reference files (e.g. references/workflows.md, references/experiment-design.md) with clearly signaled links, so SKILL.md becomes a lean overview with navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Roughly 150 of the 190 lines are capability catalogs ("Descriptive statistics, inferential statistics, and hypothesis testing", "Python ecosystem: pandas, NumPy, scikit-learn") that enumerate knowledge Claude already possesses, plus a Behavioral Traits and Knowledge Base section of pure padding. It sits between "severely verbose/heavily padded" (1) and "mostly efficient" (3): the padding is extensive but takes the form of lists rather than explanations of concepts. | 2 / 5 |
Actionability | The Instructions are entirely abstract ("Apply relevant best practices and validate outcomes"), and the Response Approach steps are generic ("Apply appropriate methods based on data characteristics and business goals"). The Example Interactions offer minimal concrete anchoring of scope, but no executable guidance, specific commands, or code anywhere — "minimal concrete guidance; high-level hints but missing the specific steps". | 2 / 5 |
Workflow Clarity | The eight-step Response Approach is a coherent, sensibly ordered sequence that does name validation (step 4, "Validate results rigorously through statistical testing and cross-validation"), so validation is not absent (ruling out 2). But the checkpoints are implicit and the steps lack the concrete commands or explicit decision/feedback points of level 4. | 3 / 5 |
Progressive Disclosure | No bundle files exist and the body references no external files at all; the ~150-line capability catalog is exactly "content that clearly belongs in separate files" inlined into SKILL.md. The section headers provide some structure (keeping it above 1), but with zero reference architecture it cannot reach level 3, which presumes references are present. | 2 / 5 |
Total | 9 / 20 Passed |