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nature-skills

by @Yuan1z0825v
4.5(120)

This is an AI-powered toolkit designed to help researchers efficiently prepare and publish academic papers. It offers functionalities such as Nature-standard figure generation, academic prose polishing, citation management, data availability statements, reviewer response drafting, and paper-to-PPT conversion, comprehensively enhancing the quality and efficiency of research output.

academic-publishingscientific-writingdata-visualizationai-toolsresearch-supportGitHub
Installation
git clone https://github.com/Yuan1z0825/nature-skills.git
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Before / After Comparison

1
Before

Manually adjusting figure formats, repeatedly polishing academic text, organizing citations, and drafting reviewer responses are extremely time-consuming, and it's challenging to ensure all details meet the stringent standards of top-tier journals.

After

Utilizing AI tools to automatically generate Nature-standard figures, intelligently polish manuscripts, efficiently manage citations, and assist in drafting high-quality reviewer responses significantly shortens the paper preparation cycle and boosts publication success rates.

SKILL.md

nature-skills

📢 课题组诚招“医学 + AI”实习生

Star History

Star History Chart

Skill index

SkillStatusPurposeTrigger keywords
nature-figureStablePublication-ready matplotlib figures"Nature figure", "publication plot", "scientific figure"
nature-polishingStableAcademic prose polishing to Nature style"Nature style", "polish", "academic writing"
nature-citationBetaStrict Nature / CNS-family citation retrieval with ENW, RIS, and Zotero RDF export"Nature citation", "CNS citation", "text citation", "supporting references", "Zotero RDF"
nature-dataDraftNature Data Availability statements, repository plans, and FAIR checks"Data Availability", "repository", "FAIR metadata", "data availability statement"
nature-responseBetaPoint-by-point reviewer response letters with comment triage, action mapping, and risk checks"response to reviewers", "rebuttal letter", "major revision", "审稿意见回复"
nature-paper2pptBetaChinese PPTX decks from scientific papers"paper PPT", "journal club", "paper to slides", "paper presentation"

Adding a new skill? Follow the contribution guide at the bottom of this file.


nature-figure

What it does — Generates multi-panel matplotlib figures that match Nature journal visual standards: correct typography, semantic colour palette, editable SVG output, and non-redundant panel information architecture.

Example output gallery — Five dense, simulated Nature-style result figures are included in the nature-figure gallery: material/mechanism, spatial imaging, in vivo efficacy, single-cell systems and perturbation validation.

Chart-type atlas — The nature-figure chart atlas classifies 10 supported chart families, including bar, line, heatmap, scatter/bubble, radar/polar, distribution, forest/interval, area/stacked, image-plate and network/matrix layouts.

Material design and physical validationSpatial imaging and uptakeIn vivo efficacy and tolerabilitySingle-cell systems figurePerturbation validation

Built from — Production scripts from papers published in Nature Machine Intelligence and top ML/bioinformatics venues (figures4papers).

Key rules enforced

  • Three mandatory rcParams must always appear first:
    plt.rcParams['font.family'] = 'sans-serif'
    plt.rcParams['font.sans-serif'] = ['Arial', 'DejaVu Sans', 'Liberation Sans']
    plt.rcParams['svg.fonttype'] = 'none'   # text stays as <text> nodes, not paths
    
  • Primary output is always .svg; .png at 300 dpi is a secondary raster preview.
  • Multi-panel figures follow a three-level information hierarchy: overview → deviation → relationship. No two panels may answer the same scientific question.

Reference files

skills/nature-figure/
├── README.md
├── SKILL.md
└── references/
    ├── api.md            PALETTE, helper signatures, validation rules
    ├── design-theory.md  Typography, layout, export policy, anti-redundancy rules
    ├── common-patterns.md Ultra-wide panels, legend axes, print-safe bars
    ├── tutorials.md      End-to-end walkthroughs (bars, trends, heatmaps)
    └── chart-types.md    Radar, 3D sphere, scatter, fill_between, log-scale

Supported chart types — Stacked bar, grouped bar, horizontal ablation bar, trend/line, sequential heatmap, diverging z-score heatmap, bubble scatter, radar/polar, 3D sphere illustration, fill-between area, log-scale bar, GridSpec multi-panel.


nature-polishing

What it does — Transforms academic draft text (including Chinese → English translation) into prose matching Nature journal conventions: ≤ 30-word sentences, section-aware tense and hedging, precise vocabulary, correct citation practice, and British English.

Built from — Close reading of five Nature s41586 papers (2026) and a graduate-level scientific English writing course; 25 rules extracted across sentence architecture, paper structure, vocabulary, citation integrity, house style, and AI ethics.

Key rules enforced

DomainCore rule
Sentence lengthEvery sentence ≤ 30 words; count individually; last sentence most likely to fail
Hedging calibrationMatch claim strength to evidence: demonstratesuggestmay reflect
Section tenseResults = past tense + quantitative detail; Discussion = hedging + mechanism
Citation integrityCite only sources personally read and verified; four attribution types
Overclaim detectionFlag absolutes, unwarranted causation, scope expansion, unverified "first" claims
British Englishsignalling, colour, analyse, programme, modelling, behaviour

12-step polishing workflow

Sentence split → Section ID → Hourglass check → Tense audit → Sentence edit → Vocabulary upgrade → Template check → Citation audit → House style → Overclaim → Proofreading → Plain-text output

Reference files

skills/nature-polishing/
├── README.md
└── SKILL.md    25 rules + 12-step workflow (loaded by Claude automatically)

nature-citation

What it does — Converts manuscript text or standalone claims into strict Nature / CNS-family citation candidates, then exports one reference-manager-ready file in ENW, RIS, or Zotero RDF. It can also generate an HTML screening page for year filtering, citation selection, and format-specific download.

Built from — Crossref metadata retrieval, DOI record export, and journal-family filtering logic for Nature Portfolio, the AAAS Science family, and Cell Press.

Key rules enforced

DomainCore rule
Scope filteringRestrict to Nature Portfolio, Science family, Cell Press, or flagship-only journals
SegmentationSplit long text into citable claim units with stable segment IDs
Search disciplineTranslate Chinese claims into English scientific concepts; prefer precision over volume
Support gradingDistinguish strong, partial, background, limiting, and metadata-only support
Export integrityDo not fabricate DOI, pages, volume, issue, or journal metadata
Download optionsSupport one-file export in ENW, RIS, or Zotero RDF

Reference files

skills/nature-citation/
├── README.md
├── SKILL.md
├── references/
│   ├── journal-scope.md
│   ├── ris-endnote.md
│   └── search-strategy.md
└── scripts/
    └── nature_citation.py

Example workflow — Segment a paragraph, search in-scope citations, review candidates in the HTML browser, then download only the selected records as ENW, RIS, or Zotero RDF.


nature-data

What it does — Prepares and audits Data Availability statements, repository plans, dataset citations, and FAIR metadata checks for Nature-family and Springer Nature submissions. It is bilingual-aware: Chinese author notes such as "data availability statement", "request from corresponding author", "raw data", "restricted data", and "public database" are converted into precise submission-ready English with Chinese action notes.

Built from — Springer Nature research data policy, Nature Portfolio reporting standards, Scientific Data repository and citation practice, the FAIR Guiding Principles, and DataCite metadata conventions.

Key rules enforced

DomainCore rule
Data AvailabilityMap every result-supporting dataset to a durable access route
Repository strategyPrefer mandated or discipline-specific repositories with persistent identifiers
Restricted dataState the restriction reason, controller, review route, and access conditions
Dataset citationsCite public datasets with DataCite-style creator, title, repository, year, and identifier metadata
FAIR metadataCheck identifiers, licence, README/data dictionary, provenance, version, and reuse conditions
Chinese alignmentTranslate intent rather than literal wording; flag vague "reasonable request" phrasing

Reference files

skills/nature-data/
├── README.md
├── SKILL.md
├── agents/
│   └── openai.yaml
└── references/
    ├── chinese-author-alignment.md
    ├── fair-metadata-checklist.md
    ├── policy-principles.md
    ├── repository-and-identifiers.md
    ├── source-basis.md
    └── statement-patterns.md

nature-response

What it does — Drafts, audits, and revises point-by-point reviewer response letters for Nature-family and high-impact journal manuscript revisions. It treats the response letter as an editor-facing verification document: every reviewer concern is assigned a stable ID, classified, mapped to an action, and tied to manuscript evidence, a revision location, or an unresolved author-input flag.

Built from — Nature editorial process guidance, Nature-family revision-package instructions, Springer Nature rebuttal advice, and transparent peer-review considerations.

Key rules enforced

DomainCore rule
CompletenessEvery reviewer comment receives an ID and a response, cross-reference, or unresolved flag
Action mappingEach reply maps to a concrete manuscript action such as ACCEPT_TEXT, ACCEPT_ANALYSIS, SOFTEN_CLAIM, or AUTHOR_INPUT_NEEDED
TraceabilityClaimed changes must cite a section, page, line, figure, table, supplement, citation, or visible placeholder
FactualityDo not invent experiments, analyses, citations, line numbers, figure panels, editor instructions, or manuscript changes
ToneUse cooperative, evidence-forward language; disagree only with scientific or scope-based reasoning
Chinese alignmentConvert Chinese author notes into English response prose plus Chinese confirmation items when needed

Reference files

skills/nature-response/
├── README.md
├── SKILL.md
├── references/
│   ├── action-mapping.md
│   ├── chinese-author-alignment.md
│   ├── comment-taxonomy.md
│   ├── difficult-cases.md
│   ├── intake-and-routing.md
│   ├── qa-checklist.md
│   ├── response-structure.md
│   ├── source-basis.md
│   └── tone-and-stance.md
├── tests/
    ├── conflicting-reviewers.md
    ├── defensive-draft-audit.md
    ├── evaluation-summary.md
    ├── impossible-experiment.md
    ├── major-revision-missing-evidence.md
    ├── minor-revision.md
    └── rubric.md
└── examples/
    ├── conflicting-reviewers.md
    ├── major-revision-with-missing-evidence.md
    └── minor-revision.md

nature-paper2ppt

What it does — Turns a scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes into a concise Chinese .pptx presentation for journal club, group meeting, lab meeting, paper sharing, or thesis seminar.

The skill identifies the paper type and central argument, selects only figures and tables that support the evidence chain, writes Chinese slide titles, bullets, captions, takeaways and speaker notes, creates the actual PPTX deck, and runs lightweight package QA.

Key rules enforced

DomainCore rule
NarrativeUse the paper's scientific argument as the slide spine, not the manuscript section order
Paper typeClassify the paper before choosing claim-first, problem-to-solution, workflow-to-validation, or evidence-map logic
FiguresUse figures as evidence; crop or split dense panels rather than shrinking them into unreadable slots
OutputBuild a real .pptx as the primary deliverable, with Chinese text and speaker notes
QAReopen or inspect the PPTX package, record slide count, embedded media, notes, and any rendering limits
IntegrityDo not fabricate results, methods, numbers, datasets, mechanisms, or figure details

Reference files

skills/nature-paper2ppt/
├── README.md
└── SKILL.md

Shared design principles

All skills in this collection adhere to the following:

  1. Primary sources only — rules are grounded in published Nature content or official journal guidelines, not general style preference.
  2. Explicit over implicit — every rule is stated with a rationale, not just asserted.
  3. Section-aware — academic writing and figures both require context-sensitivity; each skill applies different logic depending on which part of a paper is being handled.
  4. Output-first — every skill returns something immediately usable: copy-paste prose, a .svg file, a .pptx deck, or a concrete recommendation. No intermediate planning documents.
  5. Extensible by design — each skill is self-contained in its own directory; adding a new skill requires no changes to existing ones.

Adding a new skill

To add a skill to this collection:

1. Create a directory

nature-<topic>/

2. Minimum required files

FileRequiredPurpose
SKILL.mdYesFrontmatter (name, `des

...

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Installs6.6K
Rating4.5 / 5.0
Version
Updated2026年5月23日
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Timeline

Created2026年5月11日
Last Updated2026年5月23日