Conciseness

The body is dense with genuinely non-obvious domain knowledge (tool signatures, Forge cost tables, API response shapes, sign conventions) and avoids explaining concepts Claude already knows. Not a 5 because there is some narrative padding that could be trimmed — e.g. the motivating KRAS eval anecdote in Step 4 ('The eval that motivated this skill... got qualitatively similar answers') and some justificatory prose around the AlphaMissense options — but it is efficient overall, well above the 'noticeably verbose' level 3.

Actionability

Nearly all guidance is executable: complete function definitions (categorize, sae_drop_per_variant, parse_bin_list, am_per_variant_matrix), concrete tool calls with real signatures and return shapes, and a runnable sweep. Not a 5 because Step 6's plotting snippet references undefined variables (s_neutral, s_disruptive, p — the defined names are s_neutral_finite/s_disruptive_finite), and option A never shows how wt_pooled/variant_pooled are obtained, so it is not fully copy-paste ready.

Workflow Clarity

Steps 1–6 are explicitly sequenced, and Step 3.5 is a hard validation gate for a batch compute ('Insufficient predictor scores... INSTRUCTS to INVESTIGATE THE PREDICTOR COMPUTATION STEP before continuing') with a feedback loop — 'do not paper over... debug the predictor computation step (re-run, check API keys, check log files)'. The mandatory sign-convention double-check and the robustness sweep add further checkpoints, matching the top anchor including the batch-operation validation requirement.

Progressive Disclosure

No bundle files exist, and the single SKILL.md is well structured with clear section headers, tables, and a cross-reference table pointing one level deep to sibling skills. Not a 5 because the file is ~440 lines of monolithic content — the per-predictor option details (especially the AlphaMissense response shape and bin-parsing code) would naturally live in a references/ file that the body currently inlines.

Specificity

The description lists multiple concrete, specific actions — 'Computes per-variant predictor scores, splits variants into neutral vs disruptive groups by DMS effect, runs a Mann-Whitney U test on the predictor scores, and sweeps the stratification thresholds for robustness' — with comprehensive coverage and no vague padding. Not a 4 because the action list is complete rather than having minor gaps.

Completeness

Clearly answers both questions: 'what' via the enumerated concrete actions and 'when' via the explicit trigger clause 'Use when you need to know whether a predictor's scores track real functional disruption on a specific protein.' Both are concrete and explicit, matching the top anchor.

Trigger Term Quality

Good keyword coverage: 'variant-effect predictor', 'AlphaMissense', 'ESM-C SAE', 'deep mutational scanning (DMS)', 'Mann-Whitney U test', 'functional disruption' are natural terms a researcher would say. Not a 5 because common synonyms like 'benchmark', 'correlate with', or 'validate against DMS' phrasings users might naturally use are absent.

Distinctiveness Conflict Risk

The description carves a clear niche — validating per-variant numeric predictors against experimental DMS data — naming specific tools (AlphaMissense, ESM-C SAE, EVE), so it is unlikely to trigger for the wrong skill. Not a 4 because the tool names and statistical framing leave minimal overlap with adjacent analysis skills.