Conciseness

The body is dense with non-obvious domain knowledge (tool signatures, Forge cost tables, sign conventions, API response shapes) and mostly avoids explaining concepts Claude already knows, but sections like the full AlphaMissense response dump and the 'eval that motivated this skill' anecdote could be trimmed — fitting the 4-anchor 'minor instances of over-explanation' rather than the 5-anchor's every-token-earns-its-place.

Actionability

Nearly all guidance is executable, copy-paste-ready code with real tool calls and parameters, but there are minor gaps: Step 6's plotting code references 's_neutral'/'s_disruptive' while Steps 3.5-4 define 's_neutral_finite'/'s_disruptive_finite', and option C leaves the log-odds computation to the reader — matching the 4-anchor 'concrete code with minor gaps' rather than fully copy-paste-ready.

Workflow Clarity

Steps 1-6 are clearly sequenced with an explicitly MANDATORY validation checkpoint (Step 3.5's NaN coverage hard gate that raises ValueError with 'INVESTIGATE THE PREDICTOR COMPUTATION STEP before continuing'), error-recovery feedback ('debug the predictor computation step (re-run, check API keys, check log files)'), a sign-convention double-check, and a robustness sweep — matching the 5-anchor's explicit validation steps and feedback loops.

Progressive Disclosure

The 440-line body is well-sectioned but entirely monolithic: no bundle files exist (no references/, scripts/, or assets/), and content that clearly belongs in separate files — the ~80-line AlphaMissense option B with bin-parsing code, the four predictor options, the interpretation tables — is all inlined; it also cites 'tests/integration/test_dms_pipeline_e2e_kras.py', which is not present in the bundle. This fits the 3-anchor 'content that should be separate is inline' rather than the 4-anchor's appropriately split structure.

Specificity

The description lists multiple concrete, comprehensive 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' — going beyond the 4-anchor's 'minor gaps in coverage' by enumerating the full pipeline.

Completeness

Both questions are explicitly answered: the 'what' is the enumerated compute/stratify/test/sweep pipeline, and the 'when' is concrete — 'Use when you need to know whether a predictor's scores track real functional disruption on a specific protein.'

Trigger Term Quality

Good natural-term coverage — 'AlphaMissense', 'ESM-C SAE', 'EVE', 'deep mutational scanning (DMS)', "predictor's scores track real functional disruption" — but a few phrases practitioners naturally say ('missense', 'benchmark', 'correlate', 'MaveDB') are absent, matching the 4-anchor rather than the 5-anchor's comprehensive synonym coverage.

Distinctiveness Conflict Risk

A clear niche (statistical validation of variant predictors against DMS data) with domain-specific triggers, but the broad 'or any per-variant numeric score' clause and closely related sibling skills in the same collection (e.g. protein-sae-variant-interpretation) leave minor overlap risk, fitting the 4-anchor 'mostly distinct'.