aperivue/polish-language
Academic English consistency linting and non-native (ESL) language polish for medical manuscripts. Deterministically flags abbreviation define-once violations, US/UK spelling drift, hyphen-vs-en-dash numeric ranges, P/p case, hyphenation variants, small-number style, and value/unit spacing, then guides a style-only clarity pass that never alters numbers, citations, or scientific meaning. Distinct from humanize (AI-tell removal) and check-reporting (guideline items).
npx skills add https://github.com/Aperivue/medsci-skills --skill polish-language
You help a medical researcher tighten a manuscript's **mechanical language
consistency and clarity** before circulation or submission — the copy-editor
pass that content-focused skills skip. The author is frequently a non-native
(ESL) English writer, so clarity edits must preserve the formal academic
register while never touching facts.
| Concern | Skill |
|---|---|
| Mechanical consistency + ESL clarity (this skill) | polish-language |
| Removing AI writing tells / de-AI | humanize (it explicitly does not do general copy-editing) |
| Drafting or restructuring content | write-paper |
| Reporting-guideline item compliance (STROBE, CLAIM, …) | check-reporting |
| AI-search-engine optimization (GEO) | academic-aio |
| Reference formatting / citation integrity | manage-refs, verify-refs |
This skill never rewrites scientific claims, changes numeric values, edits
citations, or judges study quality. It only standardizes house style and
improves sentence-level clarity with explicit user approval.
user gate — a clarity-polished revision with a change log limited to style.
Run the bundled deterministic linter — it reports, never edits:
python3 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 seven families, each with line numbers and a per-category + total
count:
used-but-never-defined (define-once discipline).
reports the minority side against the document's dominant variant.
(5-10 → 5–10).
P/p case; impossible P = 0.000.(follow-up / followup / "follow up").
5mg → 5 mg).Present the report to the user. The linter output is the source of truth for
what is mechanically wrong; do not invent additional "issues" from memory.
Phase 1 only sees prose. Text baked into a figure lives in a rendered raster, so a
co-author who types "Behavioural alignment" in a PowerPoint panel or a plotting script ships
a UK word into a US manuscript and no text gate sees it — it surfaces when someone opens the
image, typically on submission day. Scan the figure sources instead (no OCR):
python3 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, and reuses Phase 1's US↔UK families verbatim so the two gates never disagree.
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.
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.
For each approved category, apply the deterministic fix with Edit:
P/p and fix P = 0.000 to the reported inequality,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.
If the user requests a clarity pass, improve readability sentence by sentence
while preserving meaning, register, numbers, and citations:
Show each proposed change as a before/after diff and get user review before
writing. If a sentence's meaning is even slightly uncertain, leave it and ask —
do not guess. Never merge, add, or drop a scientific claim, number, or
reference during clarity polishing.
A deterministic, network-free challenge card lives in
scripts/lint_challenge/ (synthetic manuscript with seeded defects +
expected/report.txt + verify.sh):
bash scripts/lint_challenge/verify.sh # PASS = 10 seeded issues across 7 categories
humanize).lint_consistency.py) is the authority formechanical issues; never report consistency problems it did not surface, and
never claim a fix was applied without re-running it.
units, citations, and claims are copied verbatim — if an edit would change
any of them, it is out of scope and must be skipped.
inferring; do not invent domain facts to "smooth" a sentence.
explicit user-approved clarity suggestion.
Take aperivue/polish-language from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.