Conciseness

The body is lean and assumes Claude's competence: it teaches only non-obvious, pipeline-specific knowledge (arcsinh value range [-1, 15], nan_to_num after z-score scaling, Leiden timeout above 50K cells) with terse tables and step summaries. Not a 4 because there is no over-explanation of known concepts or padding that could be trimmed.

Actionability

Approach 1 provides a complete CLI invocation with every flag and default documented, and Approach 2's imports reference functions that all exist in scripts/. Not a 5 because the modular imports lack sys.path/path setup so they are not copy-paste ready, and the CLI template requires substituting <this-skill-dir> and <input_path> placeholders.

Workflow Clarity

Steps 1-7 are clearly sequenced with per-step methods, and Important Notes supplies validation checkpoints ("Check value ranges before applying arcsinh", "Always run nan_to_num after z-score"). Not a 5 because there is no error-recovery feedback loop describing what to do when a step fails or how to verify the final report; not a 3 because checkpoints are explicit, if collected in a notes section.

Progressive Disclosure

The body is a concise overview with four well-signaled, one-level-deep references (all verified to exist with no cross-nesting), each annotated with its purpose, and detailed content appropriately split into references/ and scripts/. Matches the top anchor: clear overview, easy navigation, content appropriately placed.

Specificity

Names four concrete actions ("perform quality control, dimensionality reduction, clustering, or marker analysis") plus the domain technologies (CyTOF, scRNA-seq, flow cytometry, proteomics), matching the 'several specific actions with minor gaps' anchor. Not a 5 because normalization and report generation are only implied via trigger phrases rather than stated capabilities; uses third person so no voice penalty.

Completeness

Explicitly answers 'when' ("This skill should be used when the user asks to...") with concrete quoted trigger phrases, and 'what' ("perform quality control, dimensionality reduction, clustering, or marker analysis on single-cell biology data"), matching the top anchor's structure. Not a 4 because both halves are present with fully concrete triggers, not just implicit ones.

Trigger Term Quality

Eight quoted natural user phrases ("run initial analysis", "QC my data", "explore my dataset", "do exploratory data analysis") plus modality synonyms give good keyword coverage. Not a 5 because file extensions users would mention (.fcs, .h5ad, .csv) are absent, which the top anchor explicitly expects.

Distinctiveness Conflict Risk

Clear single-cell-biology niche with modality-specific triggers gives minimal conflict with unrelated skills. Not a 5 because generic phrases like "explore my dataset" and "do exploratory data analysis" could also match general EDA or bioinformatics skills.