Content
78%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 well-structured, highly actionable body with verified one-level-deep references, clear when-to-read signals, and executable code throughout. The main weakness is conciseness: version/date specifics recur across nearly every section and several best practices are stated multiple times instead of being consolidated or moved to a versioning/deprecated section.
Suggestions
Consolidate time-sensitive specifics (pinned build '2025-11-08', SDK '1.18.0', schema '2.4.0', verification date) into a single versioning section or an 'old patterns' note, and have inline examples reference that section instead of repeating the literal build date in every code snippet.
Deduplicate repeated guidance: state the is_primary_data filter and census_version pinning advice once in Key Concepts and have Troubleshooting cross-reference them rather than restating the same filters and code.
Tighten the Use Cases section by removing examples that repeat code already shown in Key Concepts (e.g., the get_obs value_counts and get_anndata examples), keeping only cases that introduce new patterns.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is largely efficient and assumes domain competence (no padding explaining what single-cell data is), but time-sensitive specifics are pervasive rather than consolidated — the pinned build '2025-11-08' appears in nearly every code example, plus '2026-09-30', 'cellxgene-census==1.18.0', and 'schema 2.4.0' scattered across sections with no deprecated/old-patterns section. Advice is also repeated (the is_primary_data filter appears in three sections; version-pinning guidance in three). This fits 'mostly efficient but includes some unnecessary explanation or could be tightened'; it is not 4 because the repetition and scattered version/date details go beyond minor trimmable instances. | 3 / 5 |
Actionability | Nearly every section ships copy-paste-ready executable code: install commands, open_soma/get_obs/get_anndata queries, axis_query size estimation, presence-matrix slicing, a full tiledbsoma-ml dataloader loop, and a complete scanpy rank_genes_groups workflow. The common cases (explore, query expression, ML batches, cross-tissue analysis) are all covered with concrete runnable snippets; the only placeholder is the intentional '# Training logic' comment, so this is not 4. | 5 / 5 |
Workflow Clarity | There is a clear sequence (resolve/pin the release version, explore metadata, estimate query size, then query, escalating to out-of-core processing), plus explicit checkpoints like counting rows before loading and checking the presence matrix, and a Troubleshooting section with error-recovery feedback loops (memory errors, gene not found, duplicate cells). It falls short of 5 because the eight detailed workflow patterns and their step-by-step validation are delegated to the reference file, and there is no consolidated checklist tying the sequence together inline. | 4 / 5 |
Progressive Disclosure | The SKILL.md body is an overview that indexes the eight workflow patterns with one-line summaries pointing to references/core_workflow_patterns.md, moves schema detail to references/census_schema.md and pattern examples to references/common_patterns.md (both with explicit '**When to read:**' labels), and points to references/api_access.md for endpoint contracts — all four files verified to exist and one level deep. Navigation is easy and content is appropriately split, matching the top anchor; the single sibling cross-link from core_workflow_patterns.md to common_patterns.md does not create deep nesting. | 5 / 5 |
Total | 17 / 20 Passed |