nature-polishing
Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article…
Skill by Galaxy-Dawn
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/galaxy-dawn-nature-polishing
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing, research, writing-editing, translation
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/nature-polishing
What's inside
- Skill name
nature-polishing- Description
- Polish, restructure, or translate academic prose into Nature-leaning English using writing-strategy principles, curated Nature/Nature Communications article patterns, and phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English.
- License
- MIT
- Instructions
- 391 lines in SKILL.md · view on GitHub
Files (7)
- README.md
- SKILL.md
- phrasebank-playbook.md · references/
- published-article-patterns.md · references/
- section-moves.md · references/
- style-guardrails.md · references/
- writing-strategy.md · references/
SKILL.md (first lines)
# Nature-Style Academic Polishing Use this skill to improve scientific writing at two levels: - `main strategy`: paper architecture, published-article patterns, section logic, reader workflow, evidence thresholds, and ethics - `reference support`: reusable phrase families, move patterns, transitions, and style checks The main strategy should come from the course notes in `Chapter1-Week1-7` and the curated article-pattern reference. The wording layer should come from `Academic Phrasebank`. ## Default stance - Language serves argument. Do not polish sentences while leaving the reasoning broken. - Write with empathy for the reader: relevance first, then novelty, then trust, then reuse, then meaning. - There should be no mystery for the writer, but there may be one for the reader. - Do not invent data, references, mechanisms, or novelty claims. - Do not let AI draft the paper's core scientific argument from scratch. - If the draft is Chinese or structurally rough, reconstruct the logic first and the prose second. - Avoid em dashes in polished output by default. Prefer commas, parentheses, or full stops. Use colons sparingly unless the user explicitly asks to preserve dash-based punctuation or wants a colon-led style. ## Mined writing memory For academic prose, check the active installed `skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md` under the current client's skill home. Use only source-attributed entries that fit the section and venue, alongside this skill's curated references. Treat them as optional style and structure examples. Preserve the author's claims and evidence, follow current journal instructions, and do not copy source phrasing. If the memory has no relevant entries, continue without it. ## When to open extra files These files are reference support. Use them after the section's rhetorical job is clear. | File | Open when | |---|---| | [references/published-article-patterns.md](references/published-article-patterns.md) | You need Nature/Nature Communications article-level writing patterns for abstracts, introductions, Results, Discussion, conclusions, or titles | | [references/writing-strategy.md](references/writing-strategy.md) | You need paragraph- or section-level argument repair before sentence polishing | | [references/section-moves.md](references/section-moves.md) | You need section-specific move orders or phrase patterns derived from Academic Phrasebank | | [references/phrasebank-playbook.md](references/phrasebank-playbook.md) | You need hedging, transition, evidence, limitation, or future-work phrase families | | [references/style-guardrails.md](references/style-guardrails.md) | You need academic-style checks, paragraph/sentence checks, article use, register, or mechanics | ## Core architecture ### 1. Identify the paper type first Before editing, determine what kind of paper or section this is. - `Research paper`: the reader asks why the phenomenon matters, what was done, what was found, and what it means. - `Methods paper`: the reader asks whether the method works, whether it is reproducible, and whether it is better under a fair comparison. - `Hypothesis-based work`: the argument tries to establish or rule out a causal explanation. - `Algorithmic or device work`: the argument proposes a procedure, tool, or system and must show that it performs reliably and advantageously. Do not use one narrative logic for all paper types. For article-level rewrites, especially abstracts, introductions, Results openings, Discussion paragraphs, conclusions, and titles, also apply the writing patterns in `references/published-article-patterns.md`. ### 2. Write for the reader, not for the draft chronology Most readers follow a stable sequence: 1. Is this relevant to me? 2. What is new here? 3. Do I trust it? 4. Can I reuse it? 5. What does it mean, and where are the boundaries? Polishing should help the paper answer these questions in this order. ### 3. Use the hourglass structure Strong papers often mirror an hourglass: - `Introduction`: open broadly, then narrow to the specific gap, question, hypothesis, methods, and study - `Discussion/Conclusion`: widen again, connecting the findings back to the literature and explaining how the knowledge gap was filled If a paragraph or section violates this architecture, rebuild it before polishing wording. ### 4. Use the correct writing order For a research article, a productive writing order is: 1. Results 2. Introduction and Conclusion 3. Title 4. Discussion 5. Materials and Methods 6. Authors 7. Abstract For a methods paper, a productive writing order often begins with: 1. Methods 2. Results 3. Introduction 4. Conclusion 5. Discussion 6. Abstract The skill should follow the logic of evidence and argument, not the raw order in which the user drafted sentences. ### 5. Protect the core argument The paper's core argument includes: - the scientific question the paper actually answers - why that question matters - how the work differs from existing research - what the results imply - how the main line of reasoning unfolds AI may help polish, structure, or compare phrasings. AI should not invent or author the core argument. If the argument is weak or unclear, expose that weakness rather than hiding it under polished language. ### 6. Diagnose the failure mode before editing Before rewriting, identify the main problem:
From Galaxy-Dawn/claude-scholar, MIT.
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Featured in
Signals
- Stars
- 5,894
- Forks
- 461
- Open issues
- 1
- Last commit (this folder)
- Sep 23, 2026 (1 month ago)
- Last release
- Feb 25, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/Galaxy-Dawn/claude-scholar
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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nature-polishing skill. Agent Mart. https://agentmart.dev/skills/galaxy-dawn-nature-polishing (last updated 2026-10-24)