Creator · Yuan1z0825
Last updated · Sep 2, 2026
Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese
Creator · Yuan1z0825
Last updated · Sep 2, 2026
Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese
Creator · Yuan1z0825
Last updated · Sep 2, 2026
Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese
Creator · Yuan1z0825
Last updated · Sep 2, 2026
Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese
Sandbox only
Install targets
Codex install prompt
Install the "nature-polishing" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-polishing. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-polishing","task":"Install nature-polishing","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
39K
92/100 Quality · 79/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md router does not explicitly mention how to route LaTeX/layout requests to references/latex-layout.md, even though the description claims that coverage.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-polishingDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
Agent should check
Copy prompt
Task: Use nature-polishing in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
LLM text format
/api/skills/yuan1z0825-nature-polishing/install?format=text
Find alternatives
/api/skills/search?q=nature-polishing&limit=3
Agent prompt
Use nature-polishing for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-polishingRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-polishing
LLM text
/api/registry/manifest/yuan1z0825-nature-polishing?format=text
Install alias
/api/registry/install/yuan1z0825-nature-polishing
Recommend
/api/registry/recommend?task=Use%20nature-polishing%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
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--- name: nature-polishing description: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. ---
# Nature-Style Academic Polishing — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (core principles, paper-type playbooks, per-section guidance, language-specific rules, per-journal style). - A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the polishing logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these five steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.
Also read every file listed under `always_load`. These hold the default stance, failure-mode diagnosis, ethics, and output format that apply to every polish job.
### 2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research. - `section` — abstract / intro / results / discussion / conclusion / title / methods. May be multiple. Ask the user if it is ambiguous and matters for the polish. - `language` — en or zh-to-en. Detect from the draft itself. - `journal` — nature / nat-comms / nat-mach-intell / generic. Default: generic. Use `nature` only for flagship Nature, `nat-comms` for Nature Communications and `nat-mach-intell` for Nature Machine Intelligence (NMI). Do not route another Nature Portfolio title through flagship Nature rules.
State the detected axis values in one short line to the user before proceeding, so they can correct you cheaply.
### 3. Load the matching fragments
For each axis value, Read the file mapped in the manifest. Skip the `section` axis only if the user has supplied free-floating prose with no section context.
Do **not** read every fragment in `static/`. Load only what step 2 selected.
### 4. Polish using the loaded material
Apply the loaded fragments in this priority order, matching the `paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish` rule from `core/failure-modes.md`:
1. Paper-type playbook (architecture, writing order). 2. Section-specific job and failure modes. 3. Journal-specific framing and constraints. 4. Language-specific sentence and paragraph rules (apply last). 5. Core stance and ethics throughout.
If a paragraph's structural problem cannot be fixed without inventing content, flag it instead of papering over it.
For Results, full-main-text compression, main-versus-SI allocation, or prose added during revision, load `../nature-shared/core/main-text-discipline.md` before sentence polishing. Classify each result, retain the shortest sufficient evidence chain, and require every addition to trigger a deletion or replacement check across the affected paragraph.
For flagship Nature, Nature Communications, Nature Machine Intelligence, or another Nature Portfolio title, load the matching shared Nature-style corpus guidance:
- Results or Discussion → `../nature-shared/core/nature-results-discussion.md` - Introduction or whole-manuscript narrative → `../nature-shared/core/nature-introduction.md` - Abstract → `../nature-shared/core/nature-abstract.md`
Preserve claim escalation, the fast question funnel, Introduction–Results alignment, discovery-centred abstract compression, evidence-bound local interpretation, and cross-Results synthesis. These defaults were initially distilled from published NMI papers; treat them as corpus-derived guidance, not official policy, and obey the target journal's current rules when they differ.
For any Discussion polish or restructuring job, also load `../nature-shared/core/discussion-argument-language.md`. Use its function labels to remove Results replay, repair the movement from specific findings to bounded implications, calibrate modal and reporting verbs to evidence strength, and make limitations and future work resolve named claim boundaries. Treat it as general writing guidance, not journal policy.
### 5. Reach for references only when needed
The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest, for example when the user explicitly asks for phrasebank-style alternatives or a stricter style audit.
When the target is Nature Machine Intelligence and exact limits, availability sections, conference-extension disclosure or production checks affect the revision, load `../nature-shared/journal-formats/nature-machine-intelligence.md`.
When the job is a whole manuscript rather than a passage, or the text has already been through more than one round of editing, also load `../nature-shared/core/consistency-sweep.md`. Polishing passage by passage cannot see accumulated drift: one experimental factor under several names, the same quantity in two units, a metric at two precisions, or a superlative the paper's own table contradicts. Sweep for those before working on sentences, and repeat the sweep until a pass finds nothing new.
**Layout/typesetting (排版) requests are different.** If the user asks to fix *placement* rather than wording — loose/sparse pages, stranded headings, figures that don't fill the page or split across pages, "Float too large", multi-panel arrangement, sparse Supplementary Information — skip the prose axes (paper_type, section, language, journal) and load `references/latex-layout.md` directly. That file is self-contained: it carries the diagnosis workflow (render → contact-sheet → read the log), the float-glue and `[H]`/`\clearpage`/`placeins` patterns, and the "regenerate wide figures taller at the source" rule. Always compile and visually inspect rendered pages before and after — never judge layout from the `.tex` alone.
## Why this split
- The static layer is versioned and reviewable. Adding a new journal style or paper type is one new file plus one manifest line. - The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full 1000-line monolith. - The router itself is short on purpose. Update fragments, not this file, when adding scope.
Source provenance
Decision snapshot
38,690 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-polishing, ready for a manual X post.
nature-polishing: Polish, restructure, or translate academic prose into concise Nature-leaning English while pr... 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x
Listing + install path for nature-polishing: https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to Yuan1z0825 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
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[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Yuan1z0825
@yuan1z0825
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Install targets
Codex install prompt
Install the "nature-polishing" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-polishing. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-polishing","task":"Install nature-polishing","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
39K
92/100 Quality · 79/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md router does not explicitly mention how to route LaTeX/layout requests to references/latex-layout.md, even though the description claims that coverage.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-polishingDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
Agent should check
Copy prompt
Task: Use nature-polishing in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
LLM text format
/api/skills/yuan1z0825-nature-polishing/install?format=text
Find alternatives
/api/skills/search?q=nature-polishing&limit=3
Agent prompt
Use nature-polishing for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-polishingRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-polishing
LLM text
/api/registry/manifest/yuan1z0825-nature-polishing?format=text
Install alias
/api/registry/install/yuan1z0825-nature-polishing
Recommend
/api/registry/recommend?task=Use%20nature-polishing%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
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--- name: nature-polishing description: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. ---
# Nature-Style Academic Polishing — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (core principles, paper-type playbooks, per-section guidance, language-specific rules, per-journal style). - A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the polishing logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these five steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.
Also read every file listed under `always_load`. These hold the default stance, failure-mode diagnosis, ethics, and output format that apply to every polish job.
### 2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research. - `section` — abstract / intro / results / discussion / conclusion / title / methods. May be multiple. Ask the user if it is ambiguous and matters for the polish. - `language` — en or zh-to-en. Detect from the draft itself. - `journal` — nature / nat-comms / nat-mach-intell / generic. Default: generic. Use `nature` only for flagship Nature, `nat-comms` for Nature Communications and `nat-mach-intell` for Nature Machine Intelligence (NMI). Do not route another Nature Portfolio title through flagship Nature rules.
State the detected axis values in one short line to the user before proceeding, so they can correct you cheaply.
### 3. Load the matching fragments
For each axis value, Read the file mapped in the manifest. Skip the `section` axis only if the user has supplied free-floating prose with no section context.
Do **not** read every fragment in `static/`. Load only what step 2 selected.
### 4. Polish using the loaded material
Apply the loaded fragments in this priority order, matching the `paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish` rule from `core/failure-modes.md`:
1. Paper-type playbook (architecture, writing order). 2. Section-specific job and failure modes. 3. Journal-specific framing and constraints. 4. Language-specific sentence and paragraph rules (apply last). 5. Core stance and ethics throughout.
If a paragraph's structural problem cannot be fixed without inventing content, flag it instead of papering over it.
For Results, full-main-text compression, main-versus-SI allocation, or prose added during revision, load `../nature-shared/core/main-text-discipline.md` before sentence polishing. Classify each result, retain the shortest sufficient evidence chain, and require every addition to trigger a deletion or replacement check across the affected paragraph.
For flagship Nature, Nature Communications, Nature Machine Intelligence, or another Nature Portfolio title, load the matching shared Nature-style corpus guidance:
- Results or Discussion → `../nature-shared/core/nature-results-discussion.md` - Introduction or whole-manuscript narrative → `../nature-shared/core/nature-introduction.md` - Abstract → `../nature-shared/core/nature-abstract.md`
Preserve claim escalation, the fast question funnel, Introduction–Results alignment, discovery-centred abstract compression, evidence-bound local interpretation, and cross-Results synthesis. These defaults were initially distilled from published NMI papers; treat them as corpus-derived guidance, not official policy, and obey the target journal's current rules when they differ.
For any Discussion polish or restructuring job, also load `../nature-shared/core/discussion-argument-language.md`. Use its function labels to remove Results replay, repair the movement from specific findings to bounded implications, calibrate modal and reporting verbs to evidence strength, and make limitations and future work resolve named claim boundaries. Treat it as general writing guidance, not journal policy.
### 5. Reach for references only when needed
The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest, for example when the user explicitly asks for phrasebank-style alternatives or a stricter style audit.
When the target is Nature Machine Intelligence and exact limits, availability sections, conference-extension disclosure or production checks affect the revision, load `../nature-shared/journal-formats/nature-machine-intelligence.md`.
When the job is a whole manuscript rather than a passage, or the text has already been through more than one round of editing, also load `../nature-shared/core/consistency-sweep.md`. Polishing passage by passage cannot see accumulated drift: one experimental factor under several names, the same quantity in two units, a metric at two precisions, or a superlative the paper's own table contradicts. Sweep for those before working on sentences, and repeat the sweep until a pass finds nothing new.
**Layout/typesetting (排版) requests are different.** If the user asks to fix *placement* rather than wording — loose/sparse pages, stranded headings, figures that don't fill the page or split across pages, "Float too large", multi-panel arrangement, sparse Supplementary Information — skip the prose axes (paper_type, section, language, journal) and load `references/latex-layout.md` directly. That file is self-contained: it carries the diagnosis workflow (render → contact-sheet → read the log), the float-glue and `[H]`/`\clearpage`/`placeins` patterns, and the "regenerate wide figures taller at the source" rule. Always compile and visually inspect rendered pages before and after — never judge layout from the `.tex` alone.
## Why this split
- The static layer is versioned and reviewable. Adding a new journal style or paper type is one new file plus one manifest line. - The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full 1000-line monolith. - The router itself is short on purpose. Update fragments, not this file, when adding scope.
Source provenance
Decision snapshot
38,690 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-polishing, ready for a manual X post.
nature-polishing: Polish, restructure, or translate academic prose into concise Nature-leaning English while pr... 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x
Listing + install path for nature-polishing: https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to Yuan1z0825 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing/audit)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Yuan1z0825
@yuan1z0825
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
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Install targets
Codex install prompt
Install the "nature-polishing" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-polishing. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-polishing","task":"Install nature-polishing","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
39K
92/100 Quality · 79/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md router does not explicitly mention how to route LaTeX/layout requests to references/latex-layout.md, even though the description claims that coverage.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-polishingDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
Agent should check
Copy prompt
Task: Use nature-polishing in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
LLM text format
/api/skills/yuan1z0825-nature-polishing/install?format=text
Find alternatives
/api/skills/search?q=nature-polishing&limit=3
Agent prompt
Use nature-polishing for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-polishingRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-polishing
LLM text
/api/registry/manifest/yuan1z0825-nature-polishing?format=text
Install alias
/api/registry/install/yuan1z0825-nature-polishing
Recommend
/api/registry/recommend?task=Use%20nature-polishing%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
PASS39K GitHub stars
Stars/forks activity
PASS39K stars, 2.1K forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
High-confidence pick with strong adoption and healthy maintenance signals.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
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Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: nature-polishing description: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. ---
# Nature-Style Academic Polishing — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (core principles, paper-type playbooks, per-section guidance, language-specific rules, per-journal style). - A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the polishing logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these five steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.
Also read every file listed under `always_load`. These hold the default stance, failure-mode diagnosis, ethics, and output format that apply to every polish job.
### 2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research. - `section` — abstract / intro / results / discussion / conclusion / title / methods. May be multiple. Ask the user if it is ambiguous and matters for the polish. - `language` — en or zh-to-en. Detect from the draft itself. - `journal` — nature / nat-comms / nat-mach-intell / generic. Default: generic. Use `nature` only for flagship Nature, `nat-comms` for Nature Communications and `nat-mach-intell` for Nature Machine Intelligence (NMI). Do not route another Nature Portfolio title through flagship Nature rules.
State the detected axis values in one short line to the user before proceeding, so they can correct you cheaply.
### 3. Load the matching fragments
For each axis value, Read the file mapped in the manifest. Skip the `section` axis only if the user has supplied free-floating prose with no section context.
Do **not** read every fragment in `static/`. Load only what step 2 selected.
### 4. Polish using the loaded material
Apply the loaded fragments in this priority order, matching the `paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish` rule from `core/failure-modes.md`:
1. Paper-type playbook (architecture, writing order). 2. Section-specific job and failure modes. 3. Journal-specific framing and constraints. 4. Language-specific sentence and paragraph rules (apply last). 5. Core stance and ethics throughout.
If a paragraph's structural problem cannot be fixed without inventing content, flag it instead of papering over it.
For Results, full-main-text compression, main-versus-SI allocation, or prose added during revision, load `../nature-shared/core/main-text-discipline.md` before sentence polishing. Classify each result, retain the shortest sufficient evidence chain, and require every addition to trigger a deletion or replacement check across the affected paragraph.
For flagship Nature, Nature Communications, Nature Machine Intelligence, or another Nature Portfolio title, load the matching shared Nature-style corpus guidance:
- Results or Discussion → `../nature-shared/core/nature-results-discussion.md` - Introduction or whole-manuscript narrative → `../nature-shared/core/nature-introduction.md` - Abstract → `../nature-shared/core/nature-abstract.md`
Preserve claim escalation, the fast question funnel, Introduction–Results alignment, discovery-centred abstract compression, evidence-bound local interpretation, and cross-Results synthesis. These defaults were initially distilled from published NMI papers; treat them as corpus-derived guidance, not official policy, and obey the target journal's current rules when they differ.
For any Discussion polish or restructuring job, also load `../nature-shared/core/discussion-argument-language.md`. Use its function labels to remove Results replay, repair the movement from specific findings to bounded implications, calibrate modal and reporting verbs to evidence strength, and make limitations and future work resolve named claim boundaries. Treat it as general writing guidance, not journal policy.
### 5. Reach for references only when needed
The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest, for example when the user explicitly asks for phrasebank-style alternatives or a stricter style audit.
When the target is Nature Machine Intelligence and exact limits, availability sections, conference-extension disclosure or production checks affect the revision, load `../nature-shared/journal-formats/nature-machine-intelligence.md`.
When the job is a whole manuscript rather than a passage, or the text has already been through more than one round of editing, also load `../nature-shared/core/consistency-sweep.md`. Polishing passage by passage cannot see accumulated drift: one experimental factor under several names, the same quantity in two units, a metric at two precisions, or a superlative the paper's own table contradicts. Sweep for those before working on sentences, and repeat the sweep until a pass finds nothing new.
**Layout/typesetting (排版) requests are different.** If the user asks to fix *placement* rather than wording — loose/sparse pages, stranded headings, figures that don't fill the page or split across pages, "Float too large", multi-panel arrangement, sparse Supplementary Information — skip the prose axes (paper_type, section, language, journal) and load `references/latex-layout.md` directly. That file is self-contained: it carries the diagnosis workflow (render → contact-sheet → read the log), the float-glue and `[H]`/`\clearpage`/`placeins` patterns, and the "regenerate wide figures taller at the source" rule. Always compile and visually inspect rendered pages before and after — never judge layout from the `.tex` alone.
## Why this split
- The static layer is versioned and reviewable. Adding a new journal style or paper type is one new file plus one manifest line. - The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full 1000-line monolith. - The router itself is short on purpose. Update fragments, not this file, when adding scope.
Source provenance
Decision snapshot
38,690 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-polishing, ready for a manual X post.
nature-polishing: Polish, restructure, or translate academic prose into concise Nature-leaning English while pr... 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x
Listing + install path for nature-polishing: https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to Yuan1z0825 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing/audit)
[](https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Yuan1z0825
@yuan1z0825
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
UI-TARS Desktop
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37.0K Starsn8n
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88.5K StarsTasmota
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24.7K StarsSandbox only
Install targets
Codex install prompt
Install the "nature-polishing" agent skill from https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-polishing. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"yuan1z0825-nature-polishing","task":"Install nature-polishing","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
39K
92/100 Quality · 79/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md router does not explicitly mention how to route LaTeX/layout requests to references/latex-layout.md, even though the description claims that coverage.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
ExcellentHigh-confidence pick with strong adoption and healthy maintenance signals.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
39K GitHub stars
Repo activity
39K stars, 2.1K forks
Maintenance
4d since push
License
Apache-2.0
Install
npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add Yuan1z0825/nature-skills --skill nature-polishingDo not use when
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
Agent should check
Copy prompt
Task: Use nature-polishing in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20nature-polishing%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install
Install command: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/yuan1z0825-nature-polishing/install
LLM text format
/api/skills/yuan1z0825-nature-polishing/install?format=text
Find alternatives
/api/skills/search?q=nature-polishing&limit=3
Agent prompt
Use nature-polishing for this task. Review https://www.openagentskill.com/api/skills/yuan1z0825-nature-polishing/install, then install with: npx skills add Yuan1z0825/nature-skills --skill nature-polishingRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/yuan1z0825-nature-polishing
LLM text
/api/registry/manifest/yuan1z0825-nature-polishing?format=text
Install alias
/api/registry/install/yuan1z0825-nature-polishing
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/api/registry/recommend?task=Use%20nature-polishing%20in%20an%20agent%20workflow&limit=3
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Claude Code
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PASS4d since push
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PASSApache-2.0
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--- name: nature-polishing description: Polish, restructure, or translate academic prose into concise Nature-leaning English while preserving facts, evidence boundaries, terminology, and citation intent. Use for manuscript paragraphs, abstracts, introductions, Results, discussions, conclusions, titles, Methods, Chinese drafts, proofreading, language editing, and general academic or scientific writing. Also use to shorten bloated Results, allocate evidence across main text, captions, and Supplementary Information, prevent reviewer-driven revision accretion, reduce repeated statistics or claims, and apply paragraph-necessity checks. Covers LaTeX layout or typesetting fixes such as sparse pages, stranded headings, oversized or split figures, float errors, multi-panel arrangement, and sparse Supplementary Information via references/latex-layout.md. Trigger on 学术写作、科研写作、论文润色、SCI写作、英文论文润色、语言润色、润色、改写、学术英语、排版. ---
# Nature-Style Academic Polishing — Router
This skill is split into two layers:
- A **static layer** under `static/` that holds versioned, reusable content fragments (core principles, paper-type playbooks, per-section guidance, language-specific rules, per-journal style). - A **dynamic layer** (this file plus `manifest.yaml`) that detects the request's axes and loads only the fragments needed for the current job.
Do not try to apply the polishing logic from memory or from this router. Always load fragments from disk as described below.
## Routing protocol
Follow these five steps every time the skill is invoked.
### 1. Load the manifest and the core layer
Read [manifest.yaml](manifest.yaml). It declares the axes (`paper_type`, `section`, `language`, `journal`), the allowed values, and the file paths each value maps to.
Also read every file listed under `always_load`. These hold the default stance, failure-mode diagnosis, ethics, and output format that apply to every polish job.
### 2. Detect the axis values for this request
For each axis in the manifest, decide the value using the manifest's `detect:` hint and the user's input:
- `paper_type` — research / methods / hypothesis / algorithmic / review. Default: research. - `section` — abstract / intro / results / discussion / conclusion / title / methods. May be multiple. Ask the user if it is ambiguous and matters for the polish. - `language` — en or zh-to-en. Detect from the draft itself. - `journal` — nature / nat-comms / nat-mach-intell / generic. Default: generic. Use `nature` only for flagship Nature, `nat-comms` for Nature Communications and `nat-mach-intell` for Nature Machine Intelligence (NMI). Do not route another Nature Portfolio title through flagship Nature rules.
State the detected axis values in one short line to the user before proceeding, so they can correct you cheaply.
### 3. Load the matching fragments
For each axis value, Read the file mapped in the manifest. Skip the `section` axis only if the user has supplied free-floating prose with no section context.
Do **not** read every fragment in `static/`. Load only what step 2 selected.
### 4. Polish using the loaded material
Apply the loaded fragments in this priority order, matching the `paper type -> section job -> paragraph logic -> claim/evidence/boundary -> sentence polish` rule from `core/failure-modes.md`:
1. Paper-type playbook (architecture, writing order). 2. Section-specific job and failure modes. 3. Journal-specific framing and constraints. 4. Language-specific sentence and paragraph rules (apply last). 5. Core stance and ethics throughout.
If a paragraph's structural problem cannot be fixed without inventing content, flag it instead of papering over it.
For Results, full-main-text compression, main-versus-SI allocation, or prose added during revision, load `../nature-shared/core/main-text-discipline.md` before sentence polishing. Classify each result, retain the shortest sufficient evidence chain, and require every addition to trigger a deletion or replacement check across the affected paragraph.
For flagship Nature, Nature Communications, Nature Machine Intelligence, or another Nature Portfolio title, load the matching shared Nature-style corpus guidance:
- Results or Discussion → `../nature-shared/core/nature-results-discussion.md` - Introduction or whole-manuscript narrative → `../nature-shared/core/nature-introduction.md` - Abstract → `../nature-shared/core/nature-abstract.md`
Preserve claim escalation, the fast question funnel, Introduction–Results alignment, discovery-centred abstract compression, evidence-bound local interpretation, and cross-Results synthesis. These defaults were initially distilled from published NMI papers; treat them as corpus-derived guidance, not official policy, and obey the target journal's current rules when they differ.
For any Discussion polish or restructuring job, also load `../nature-shared/core/discussion-argument-language.md`. Use its function labels to remove Results replay, repair the movement from specific findings to bounded implications, calibrate modal and reporting verbs to evidence strength, and make limitations and future work resolve named claim boundaries. Treat it as general writing guidance, not journal policy.
### 5. Reach for references only when needed
The files under `references/` are deep references, not defaults. Open them on demand per the `references.on_demand` table in the manifest, for example when the user explicitly asks for phrasebank-style alternatives or a stricter style audit.
When the target is Nature Machine Intelligence and exact limits, availability sections, conference-extension disclosure or production checks affect the revision, load `../nature-shared/journal-formats/nature-machine-intelligence.md`.
When the job is a whole manuscript rather than a passage, or the text has already been through more than one round of editing, also load `../nature-shared/core/consistency-sweep.md`. Polishing passage by passage cannot see accumulated drift: one experimental factor under several names, the same quantity in two units, a metric at two precisions, or a superlative the paper's own table contradicts. Sweep for those before working on sentences, and repeat the sweep until a pass finds nothing new.
**Layout/typesetting (排版) requests are different.** If the user asks to fix *placement* rather than wording — loose/sparse pages, stranded headings, figures that don't fill the page or split across pages, "Float too large", multi-panel arrangement, sparse Supplementary Information — skip the prose axes (paper_type, section, language, journal) and load `references/latex-layout.md` directly. That file is self-contained: it carries the diagnosis workflow (render → contact-sheet → read the log), the float-glue and `[H]`/`\clearpage`/`placeins` patterns, and the "regenerate wide figures taller at the source" rule. Always compile and visually inspect rendered pages before and after — never judge layout from the `.tex` alone.
## Why this split
- The static layer is versioned and reviewable. Adding a new journal style or paper type is one new file plus one manifest line. - The dynamic layer keeps each invocation cheap: only the fragments relevant to this draft enter context, instead of the full 1000-line monolith. - The router itself is short on purpose. Update fragments, not this file, when adding scope.
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38,690 GitHub stars
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Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for nature-polishing, ready for a manual X post.
nature-polishing: Polish, restructure, or translate academic prose into concise Nature-leaning English while pr... 38.7K stars https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x
Listing + install path for nature-polishing: https://www.openagentskill.com/skills/yuan1z0825-nature-polishing?ref=x Install: npx skills add Yuan1z0825/nature-skills --skill nature-polishing
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Strong README/SKILL.md context
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