Conciseness

Quotes: the intro paragraph 'OpenMed de-identifies clinical text in many languages, each with a dedicated PII model, language-specific regex patterns...' and the '## Standards & references' section with a full HIPAA URL. The body is mostly lean (code, table, gotchas) but these passages are minor over-explanation that could be trimmed — anchor 4. Not 5: not every token earns its place; not 3: only isolated instances, no pervasive padding.

Actionability

Quotes: 'result = openmed.deidentify(nota, lang="es", method="replace", locale="es_ES")' with expected output shown, the German variant 'result = openmed.deidentify(befund, lang="de", method="replace")', and the runtime discovery snippet querying SUPPORTED_LANGUAGES. Fully executable, copy-paste-ready code covering the common cases — anchor 5.

Workflow Clarity

Quotes: '1. **Confirm the language is supported** by checking SUPPORTED_LANGUAGES' through '5. **Keep surrogates stable** across a document with consistent=True, seed=...'. The five-step sequence is clear with a front-loaded checkpoint, but the verification step ('verify residual risk with audit=True') appears only under 'Edge cases & gotchas' rather than as an explicit workflow step — anchor 4: most checkpoints present with a minor gap. Not 5: no explicit validate/verify step in the workflow itself; not 3: checkpoints are present and the sequence is unambiguous.

Progressive Disclosure

The body has well-organized sections ('When to use this skill', 'Quick start', 'Workflow', 'Language-specific national IDs', 'Hand-off to / from OpenMed', 'Edge cases & gotchas', 'Standards & references') with no nested references and a clear hand-off map to sibling skills. However, the ~130-line file inlines the validator table and standards links that could sit in a reference file, so the <50-line exception for a top score does not apply — anchor 4: good structure, minor organization gaps. Not 5: it is not the lean overview-plus-one-level-references pattern.

Specificity

Quotes: 'De-identify non-English clinical text on-device with OpenMed by passing lang= and locale= to deidentify()' plus named API surfaces ('SUPPORTED_LANGUAGES, get_pii_models_by_language, get_patterns_for_language, LANG_TO_LOCALE') and concrete national IDs (DNI, NIR, Steuer-ID, codice fiscale, BSN, CPF, TCKN, Aadhaar). This matches the anchor-5 'multiple specific concrete actions; comprehensive coverage'; a 4 would require coverage gaps, and the mechanism, parameters, and API surfaces are all explicitly named.

Completeness

The first sentence explicitly answers 'what' ('De-identify non-English clinical text on-device with OpenMed by passing lang= and locale= to deidentify()') and the second gives an explicit 'Use when...' clause with concrete triggers (language list, locale-aware surrogates, national IDs, support questions). This is the anchor-5 pattern; not 4, since the 'when' is fully explicit rather than improvable.

Trigger Term Quality

Quotes: 'Spanish, German, French, Italian, Portuguese, Dutch, Hindi, Telugu, Arabic, Japanese, or Turkish medical notes' and 'asks which languages OpenMed PII supports'. These are exactly the natural words a user would say (language names, 'medical notes', specific ID names), matching the anchor-5 comprehensive coverage including synonyms; score 4 would mean missing common natural terms, which is not the case.

Distinctiveness Conflict Risk

The 'non-English' scope and enumerated languages carve a clear niche, and 'Pairs with OpenMed deidentifying-clinical-text and generating-synthetic-surrogates' explicitly delineates sibling-skill boundaries. Minimal conflict risk — anchor 5; a 4 would require real overlap risk, which the explicit pairing prevents.