/polish-language

name: polish-language
description: Use when a manuscript needs a copy-edit for consistency and non-native English clarity. Flags abbreviation, US/UK spelling, en-dash range, P/p, hyphenation, number-style and unit-spacing issues, then polishes style only. AI-tell removal is /humanize.
metadata:
  triggers: "polish language, copy-edit, consistency check, ESL, non-native English, house style, abbreviation consistency, en-dash, US UK spelling, proofread manuscript, 일관성 검사, 교정"

Polish-Language Skill

Tighten a manuscript's **mechanical language consistency and clarity** before circulation or submission — the copy-editor pass content-focused skills skip. The author is often a non-native (ESL) English writer, so clarity edits keep the formal academic register and never touch facts. Manuscript edits are in English.

This skill **never** rewrites scientific claims, changes numeric values, edits citations, or judges study quality; it standardizes house style and improves sentence-level clarity, with explicit user approval for every edit. Out of scope: AI-tell removal (`humanize`, which does not do general copy-editing), drafting or restructuring (`write-paper`), reporting-guideline items (`check-reporting`), AI-search optimization (`academic-aio`), reference formatting and citation integrity (`manage-refs`, `verify-refs`), and translation.

**Input**: a manuscript or section (Markdown / plain text). **Output**: (1) the deterministic consistency report, and (2) — only after a user gate — a clarity-polished revision with a change log limited to style.

Workflow

Phase 1: Deterministic consistency lint (no LLM judgement)

Run the bundled linter — it reports, never edits:

python3 "${CLAUDE_SKILL_DIR}/scripts/lint_consistency.py" path/to/manuscript.md
# add --strict to exit non-zero when any issue is found (CI / pre-submission gate)

It flags eight families, each with line numbers and a per-category + total count:

1. **Abbreviations** — used-before-defined, defined-but-unused, defined-twice, used-but-never-defined (define-once discipline). 2. **Spelling** — mixed US/UK variants (analyze/analyse, tumor/tumour, …); reports the minority side against the document's dominant variant. 3. **Numeric ranges** — hyphen between numbers where an en-dash belongs (`5-10` → `5–10`). 4. **p-values** — mixed `P`/`p` case; impossible `P = 0.000`. 5. **Hyphenation / terminology** — variant forms of one term (follow-up / followup / "follow up"). 6. **Small numbers** — single digits 1–9 written as digits in prose. 7. **Units** — missing space between value and unit (`5mg` → `5 mg`). 8. **Thousands separator (title vs body)** — a float title writes a number with a period separator (`3.681`) that the body writes with a comma (`3,681`).

Present the report to the user. The linter output is the source of truth for what is mechanically wrong: do not invent further "issues" from memory, and label anything else you notice as an editorial suggestion, not a linter finding. The fixed rules do not settle every grammar or journal preference, so triage flags in context.

Phase 1b: Figure-SOURCE locale drift

Text baked into a figure never reaches Phase 1, so a UK word typed into a PowerPoint panel or plotting script ships in a US manuscript unseen. Scan the figure **sources** (no OCR):

python3 "${CLAUDE_SKILL_DIR}/scripts/lint_figure_locale.py" --manuscript path/to/manuscript.md --figures-dir figures/
# --spelling us|uk forces the target; otherwise it reads a `spelling:` front-matter field,
# then falls back to the body's own US/UK majority. --strict exits non-zero on any drift.

It reads `<a:t>` runs inside `*.pptx` slide XML and the text of `*.py` / `*.R` plotting scripts, with the same US↔UK families as Phase 1. `FIGURE_LOCALE_DRIFT` is **Minor** — copy-edit the source before the raster is re-exported. A missing figures directory is not an error; it exits 0 with nothing judged.

Phase 2: Triage with the user (gate)

Walk the user through the report. Some flags are author choices (a journal may mandate UK spelling, or digits for all numbers). **User approval is required** before any edit — confirm per category which to apply and which to keep. Record the decisions; do not auto-apply.

Phase 3: Apply mechanical fixes (style-only)

For each **approved** category, apply the deterministic fix with `Edit`:

• standardize spelling to the chosen variant,
• replace numeric-range hyphens with en-dashes,
• normalize `P`/`p` and fix `P = 0.000` to the reported inequality,
• unify hyphenation, spell out small numbers, add value/unit spaces,
• define each abbreviation once at first use; remove redundant redefinitions.

Re-run `lint_consistency.py` after editing — the count should drop to the issues the user chose to keep. This re-run is the verification gate; never claim a fix without it.

Phase 4: ESL clarity polish (optional, gated, style-only)

If the user requests a clarity pass, improve readability sentence by sentence while preserving meaning, register, numbers, and citations:

• split run-on sentences; fix article (a/an/the) and preposition usage;
• correct subject–verb agreement and awkward non-native phrasings;
• prefer active voice only where it does not change emphasis or claims.

Show each proposed change as a before/after diff and get **user review** before writing. Numbers, p-values, effect sizes, units, citations, and claims are copied verbatim; an edit that would change any of them is out of scope — skip it. Never merge, add, or drop a scientific claim, number, or reference. If a sentence's meaning is even slightly uncertain, leave it and ask; do not invent domain facts to smooth a sentence. Every applied change must trace to a linter flag or a user-approved clarity suggestion in the change log.

Reproducible challenge card

Deterministic and network-free (synthetic manuscript with seeded defects + `expected/report.txt`):

bash "${CLAUDE_SKILL_DIR}/scr