Content
56%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 delivers highly actionable, mostly executable code with a sensible explore-then-query workflow, but it is bloated by three sections that duplicate either the description or the references/common_patterns.md bundle file. Restructuring so the SKILL.md body is a lean overview pointing into the reference files would fix both the conciseness and progressive-disclosure deductions at once.
Suggestions
Cut the 'Common Use Cases' section (lines 429-486) and fold any non-duplicated cases into references/common_patterns.md — they almost entirely restate the Core Workflow Patterns and reference examples.
Replace the 'Key Concepts and Best Practices' section (lines 311-383) with a short list and pointers to the corresponding Best Practices items in references/common_patterns.md, which already covers them.
Move the hard-coded census_version='2023-07-25' examples into a note on version pinning (or the schema reference) rather than repeating the dated value inline, keeping time-sensitive details out of the main body.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Noticeably verbose with systematic duplication: 'When to Use This Skill' restates the description, 'Common Use Cases' near-duplicates 'Core Workflow Patterns', and 'Key Concepts and Best Practices' repeats the Best Practices section of references/common_patterns.md nearly item-for-item. The hard-coded version '2023-07-25' is time-sensitive and not placed in a deprecation/old-patterns section. Not 3 because the padding is structural and repeated across multiple sections rather than occasional. | 2 / 5 |
Actionability | Concrete, mostly executable code throughout (open_soma context manager, get_obs/get_var, get_anndata with filter syntax, axis_query chunk iteration, experiment_dataloader). Not 5 because the ExperimentDataset train/test split example references an undefined 'experiment_axis_query' variable and several snippets carry '# Work with census data' placeholder bodies. | 4 / 5 |
Workflow Clarity | Clear sequence (open census -> explore metadata -> estimate query size -> choose get_anndata vs out-of-core axis_query) with an explicit size checkpoint ('If too large (>100k), use out-of-core processing') and a troubleshooting section for error recovery. Not 5 because there is no explicit post-query verification step, though the read-only nature of the queries lowers the stakes. | 4 / 5 |
Progressive Disclosure | Both references (census_schema.md, common_patterns.md) are real, one level deep, and well signaled with explicit 'When to read' guidance, but large blocks of content that belong in those files — the Common Use Cases section and the Key Concepts best practices — are inlined in the body. Not 4 because the inlining is substantial and systematic, exceeding a 'minor organization gap'. | 3 / 5 |
Total | 13 / 20 Passed |