Nature Citation

Nature Citation

Use this skill to turn manuscript text into a defensible citation export:

• segmented text with citation candidates for each segment
• a reference-manager import file in .enw, .ris, or Zotero .rdf
• conservative evidence notes explaining whether each candidate truly supports the segment

Chinese-user operating mode

When the user writes in Chinese, asks for "Nature系列", "CNS及其子刊", "支撑文献", "补引用", "自动给出引用", "分段引用", "导出EndNote", "RIS", "Zotero", "RDF", or provides Chinese manuscript text:

• Accept the text in Chinese, but search using English concept queries unless the topic is explicitly

China-specific or Chinese-language scholarship.

• Return segment notes and evidence notes in Chinese by default.
• Preserve the exact source segment and translate it into one or more English search claims.
• Flag overclaiming clearly in Chinese: 强支撑, 部分支撑, 背景支撑, 不建议引用为该句支撑.
• Do not present a paper as supporting the claim merely because its title is related.

Default scope

Interpret journal scope from the user's wording, but keep the filter strict:

• Nature系列: search Nature Portfolio first. Include Nature, Nature [field],

Nature Communications, Communications [field], Scientific Reports, and npj journals.

• CNS: search Cell, Nature, and Science plus their major sister journals.
• CNS及其子刊 or CNS/sister journals: search only accepted flagship and subjournal titles in

Nature Portfolio, the AAAS Science family, and Cell Press.

• 只要Nature/Science/Cell正刊: restrict to the flagship journals Nature, Science, and Cell.

Do not treat merely related journals as in-scope. A title is valid only if it is in the accepted publisher-family whitelist or clearly matches the official naming pattern for that family. If the user needs an exhaustive or submission-critical boundary, verify current official journal pages before finalizing because journal portfolios change.

Source hierarchy

Use sources in this order:

1. Structured bibliographic metadata: Crossref, PubMed/NCBI E-utilities, DOI metadata. 2. Publisher pages: nature.com, science.org, cell.com, and official journal pages. 3. Full text or abstract pages, if accessible. 4. Secondary databases such as Google Scholar, Semantic Scholar, Web of Science, or Scopus only as discovery aids, not as the sole support basis.

Prefer structured APIs for metadata and publisher pages for claim verification. If metadata and publisher page disagree, preserve the DOI and journal-page facts and flag the discrepancy.

Long-article strategy

When the input text is longer than roughly 3000 characters (about 10+ segments), the skill must switch to a batched workflow to avoid timeout, context overflow, or incomplete results:

1. Auto-detect length. Count segments after segmentation. If there are more than 10 segments, switch to batch mode automatically. 2. Split by section. Prefer splitting at paragraph double-line breaks or explicit section headings (Introduction, Results, etc.) so each batch is a coherent unit, not arbitrary sentence groups. 3. Process each batch independently. Run the Python script once per batch using --batch-size or --max-segments, OR split the text externally and call the script once per chunk. Each call writes its own intermediate export file. 4. Merge results at the end. After all batches finish, combine the intermediate files into one final export. Deduplicate by DOI. 5. Minimize inline analysis. For long articles, do NOT write detailed support-grade notes for every single segment inline. Instead:

• Write a compact summary table (segment ID → best candidate → support grade).
• Point the user to the HTML visualization for full browsing.
• Only elaborate on segments where no candidate was found or evidence is contradictory.

Quick guide for Claude

Workflow

1. Segment the text

For each input text:

• Split long text into citable segments. Prefer paragraph boundaries first, then sentence boundaries.
• Keep each segment focused on one citable idea when possible.
• Preserve original order and stable segment IDs such as S001, S002, S003.
• Skip obvious non-citable connective sentences unless the user asks to cite every sentence.
• For very long text, process in batches but keep a single final mapping table.
• If the input has more than about 10 segments, prefer batch mode.

Default segmentation rules:

• Use blank lines as paragraph boundaries.
• If a paragraph is longer than about 700 characters or contains multiple claims, split into sentences.
• Merge very short fragments into neighboring text unless they contain a distinct claim.
• Keep section headings as labels, not as citable segments.

2. Parse each segment

For each citable segment:

• Extract the core claim in one sentence.
• Identify claim type: mechanism, association, method, clinical, epidemiology,

background, definition, or review-context.

• Identify entities, intervention/exposure, outcome, population/model, directionality, and boundary.
• Convert the claim into 2-4 English search queries:
• one precise query with all key terms
• one synonym query
• one broader background query
• one methods or model query if relevant

If the claim is too broad, split it into citable subclaims rather than searching the whole sentence.

3. Search candidate papers

Start with scripts/nature_citation.py when internet access is available:

python scripts/nature_citation.py \
  --text "PASTE MANUSCRIPT TEXT HERE" \
  --scope cns \
  --outdir /tmp/nature-citation \
  --format enw \
  --with-artifacts

Useful options:

• --text-file manuscript.txt: read long text from a file.
• --claim "CLAIM TEXT" or --claim-file claims.txt: treat each claim as a segment.
• --doi 10.xxxx/xxxxx or --doi-file dois.txt: export known DOI records after screening.
• --scope nature: Nature Portfolio-style journals only.
• --scope flagship: Nature, Science, and Cell only.
• --from-year 2018 --to-year 2026: constrain publication dates.
• --rows 40: raise for broad searches; keep top candidates manageable.
• --per-segment 3: number of citation candidates to keep per segment.
• --batch-size 2: process long text in smaller batches.
• --max-segments 12: cap the number of segments processed in one run.
• --max-retries 2: retry transient Crossref failures before skipping a query.
• --format enw|ris|zotero-rdf: export format. If omitted and --output-file is set, infer from suffix.
• --mailto you@example.com: use Crossref's polite pool.
• --batch-size 10: process segments in batches of N. Each batch writes an incremental export file.
• --max-segments 20: only process the first N segments. Useful for testing or section-by-section workflows.
• --sleep 0.3: seconds between Crossref requests. Default is 0.3; raise to 1.0 if rate-limited.

Long-article strategy:

• 1-10 segments: run normally.
• 11-25 segments: use batch mode and keep the HTML browser open for screening.
• 26+ segments: split by section or subsection first, then run each part separately if needed.
• For long texts, prefer the HTML browser for review and selection instead of relying only on inline notes.

When the topic is biomedical or PubMed-indexed, also search PubMed with journal filters and compare results against Crossref. Use NCBI E-utilities rate limits and include tool/email parameters if running repeated searches.

4. Evaluate whether each paper supports the segment

Use a conservative support scale:

• strong support: the paper directly tests the same relationship/mechanism/method and the result supports the segment.
• partial support: the paper supports part of the segment, a related model, or a narrower condition.
• background support: the paper supports field context, not the specific claim.
• contradictory/limiting: the paper conflicts with or narrows the claim.
• metadata-only candidate: title/metadata suggest relevance, but abstract/full text has not been checked.

Never cite a metadata-only candidate as support without checking the abstract or publisher page. If a paper is a review, label it as review/context and avoid using it as primary evidence for an experimental claim when primary articles are available.

5. Export reference-manager file

Default behavior:

• write one reference-manager file
• support publication time filters with --from-year and --to-year
• for long or ambiguous texts, use --with-artifacts so the HTML browser is available

Default file:

• references.enw: EndNote tagged export

Optional:

• references.ris: if the user requests RIS instead of ENW
• references.rdf: if the user requests Zotero RDF
• review artifacts only when explicitly requested

If the user asks to choose the download format, treat ENW, RIS, and Zotero RDF as the supported options and return only one export file unless they explicitly ask for multiple formats.

Do not invent missing fields. If DOI, pages, volume, or issue are missing, leave them absent rather than fabricating them.

6. Optional review artifacts

Generate review artifacts (HTML/TSV/JSON/report) for long or ambiguous runs. They are the primary way the user browses, filters, and selects candidates:

• Use --with-artifacts when the text is long, the query is broad, or the user needs manual curation.
• Report the HTML visualization path prominently in your final answer when artifacts are enabled.
• Generate TSV/JSON/report alongside the HTML so the user has multiple views.

7. Report results

Unless the user asks for a different format, return:

交互式引用浏览器
- [absolute path to citation_visualization.html]  ← 在浏览器中打开此文件，可筛选/选择/下载引用

检索范围
- [Nature Portfolio / Science family / Cell Press / flagship only, plus date limits]

分段引用对应关系
S001: [source segment]
  - [Author, year, title, journal, DOI]
  - 支撑等级: [strong/partial/background/limiting/metadata-only]
  - 插入建议: [e.g. after sentence / after clause]

导出文件
- [absolute path to references.enw / references.ris / references.rdf]

风险和缺口
- [missing full-text check, contradictory evidence, no direct CNS literature, etc.]

Put the HTML browser path FIRST in the report, above everything else, so the user can immediately open and browse candidates. If no suitable CNS/Nature-series paper exists, say so plainly and suggest the best nearby options from non-CNS literature only if the user wants broader coverage.

If the text is long, mention the batch strategy used, especially when you limited the run with --batch-size or --max-segments.

Search quality rules

• Prefer precision over volume. A useful answer is usually 3-8 candidates, not 50 loosely related papers.
• Use exact phrase searches only for distinctive terms; otherwise use concept terms and synonyms.
• Check journal identity. Many journals contain the word "nature" but are not Nature Portfolio journals.
• Treat citation count as a tie-breaker, not evidence of support.
• Capture retractions, corrections, and expressions of concern when visible in Crossref or publisher metadata.
• Date-sensitive topics require current searching and explicit search date.
• For medical, clinical, or safety claims, search current literature and state that citations do not replace

clinical guidance or systematic review.

Related files

Source notes

This skill is based on public bibliographic APIs and official publisher/import documentation: Crossref REST API and filters, NCBI E-utilities, EndNote RIS import options, Nature Portfolio, AAAS Science journals, and Cell Press portfolio descriptions. Verify pages at use time when exact journal coverage or current import behavior matters.

nature-citation 技能

nature-citation 用于把论文段落、手稿片段或单条科研判断转化为可审查的 Nature / CNS 系列参考文献候选，并导出可被文献管理器直接导入的文件。

这个技能支持中文输入。用户可以直接提出“分段引用”“Nature 系列引用”“CNS 及子刊”“补引用”“支撑文献”“导出 Zotero”等需求；技能会用英文科学概念检索文献，同时默认返回中文审查说明。

功能

• 将手稿拆分为可引用的 claim 单元，并生成稳定编号，例如 S001、S002、S003。
• 为每个片段生成面向 Crossref 等结构化元数据源的检索式。
• 将结果限制在 Nature Portfolio、AAAS Science family、Cell Press，或只保留旗舰刊范围。
• 为每个片段匹配候选文献，并给出建议的正文插入位置。
• 导出一个 ENW、RIS 或 Zotero RDF 文献管理文件。
• 可选生成 JSON、TSV、Markdown 和 HTML 审查材料，便于人工筛选。
• 支持长文批处理、部分检查点、失败重试和局部段落运行。
• 支持 DOI-only 导出，适合用户已经确认文献列表的场景。

来源层级

• Crossref 结构化元数据与 DOI 记录。
• 相关时使用 PubMed / NCBI E-utilities 做生物医学交叉核对。
• Nature Portfolio、AAAS Science、Cell Press 的官方出版商页面。
• 二级学术索引只作为发现线索，不能作为唯一支撑依据。

文件结构

该技能采用 router/static-dynamic 结构：SKILL.md 负责短路由，manifest.yaml 决定常驻内容和按需参考文件。nature-citation 是线性工作流，没有内容轴，因此主要由 core 常驻内容和按需 references 组成。

nature-citation/
├── SKILL.md                     # 短路由
├── manifest.yaml                # always_load core + 按需 references
├── README.md
├── static/
│   └── core/                    # 始终加载
│       ├── principles.md        # 产物、期刊范围、来源层级、检索规则
│       ├── chinese-mode.md      # 中文用户模式
│       └── workflow.md          # 7 步工作流与报告格式
├── references/                  # 按需打开
│   ├── script-usage.md          # nature_citation.py 参数与长文批处理
│   ├── journal-scope.md
│   ├── ris-endnote.md
│   └── search-strategy.md
└── scripts/
    └── nature_citation.py

适用场景

• 给摘要、引言、结果、讨论或单段文字补充引用。
• 将长文本拆成“片段-候选文献”对应表。
• 限定只检索 Nature系列、CNS、CNS及其子刊 或 只看正刊。
• 为 EndNote、Zotero 或其他文献管理器导出记录。
• 判断一句话获得的是直接支撑、部分支撑，还是背景性支撑。
• 生成 HTML 审查页，让用户按年份筛选、选择文献并下载所需记录。

长文本处理

短输入会采用普通的一次性检索流程。较长输入可以分批处理，每批完成后写入部分导出检查点，避免后续批次失败导致前面进度丢失。Crossref 临时失败会自动重试。

经验规则：

• 1-10 个片段：普通运行。
• 11-25 个片段：优先使用 batch mode。
• 26 个以上片段：优先按小节分开运行。

设计意图

该技能优先追求可辩护性，而不是候选文献数量。它的目标是帮助用户发现范围内的潜在支撑文献，而不是把元数据当成证据本身。每条导出记录都应保留真实元数据，不补造字段，并明确提示仍需人工阅读全文或摘要来确认支撑强度。

对长手稿而言，设计目标还包括运行稳定性：更小批次、更少中断、更清晰的检查点轨迹。

参考文件

• search-strategy.md：claim 拆解、支撑等级和常见检索失败模式。
• journal-scope.md：Nature / Science / Cell 家族边界与旗舰刊解释。
• ris-endnote.md：ENW、RIS、Zotero RDF 导出说明。
• scripts/nature_citation.py：本地 CLI，用于分段、Crossref 检索、导出和 HTML 审查页生成。

常用 CLI 参数

• --batch-size 2：将长文本拆成更小批次处理。
• --max-segments 12：限制一次运行处理的片段数。
• --max-retries 2：重试临时 Crossref 失败。
• --sleep 0.3：缩短请求间默认等待。
• --with-artifacts：生成 HTML、TSV、JSON 和 Markdown 审查文件。

注意事项

• 默认产物是单个文献管理文件；其他审查材料需显式开启。
• metadata-only candidate 表示仍需人工查看摘要或全文后才能引用。
• HTML 审查页可将用户选中的记录导出为 ENW、RIS 或 Zotero RDF。
• 长文本建议开启 --with-artifacts，因为 HTML 页面最方便人工筛选。
• Batch mode 会在最终导出前持续写入 .partial.enw、.partial.ris 或 .partial.rdf 检查点。

Journal Scope

The skill's default journal-family boundary is intentionally practical rather than exhaustive. Use it to find likely Nature/CNS-family candidates, then verify exact journal status on official pages if the author needs a strict portfolio definition.

Default families

Nature Portfolio

Include:

• Nature
• journals beginning with Nature , such as Nature Medicine, Nature Biotechnology,

Nature Methods, Nature Materials, Nature Genetics, Nature Communications

• Communications journals, such as Communications Biology, Communications Chemistry,

Communications Materials, Communications Earth & Environment, Communications Medicine

• npj journals
• Scientific Reports

Be careful with unrelated titles that include the common word "nature".

Science family

Include by default:

• Science
• Science Advances
• Science Translational Medicine
• Science Signaling
• Science Immunology
• Science Robotics

The AAAS Science Partner Journal program is not included by default unless the user asks for partner journals or broader AAAS coverage.

Cell Press

Include the flagship Cell, major primary-research Cell Press journals, Cell Reports titles, and Trends review journals. The local script recognizes common Cell Press titles and any title beginning with Trends in .

Because Cell Press launches and reorganizes titles over time, verify official pages for exhaustive coverage or a current journal list.

Flagship-only scope

Use only:

• Nature
• Science
• Cell

This is appropriate when the user says "只看正刊", "主刊", "flagship only", or explicitly excludes subjournals.

Official source notes

• Crossref REST API can retrieve scholarly metadata, search works, and filter exact fields such as

container-title and issn.

• NCBI E-utilities provide structured access to PubMed and other Entrez databases; observe request

frequency guidance.

• EndNote documents Reference Manager (RIS) as an import option for RIS files.
• Nature Portfolio, AAAS, and Cell Press official pages should be checked when exact current journal

coverage matters.

RIS, EndNote, and Zotero RDF Output

EndNote can import RIS files using the Reference Manager (RIS) import option. Use .ris as the default exchange format because it is plain text, widely supported, and easy to inspect.

RIS mapping for journal articles

Use these tags:

TY  - JOUR
TI  - Article title
AU  - Author, Given
T2  - Journal title
JO  - Journal title
PY  - Publication year
Y1  - YYYY/MM/DD when available
VL  - Volume
IS  - Issue
SP  - First page or article number
EP  - Last page
DO  - DOI
UR  - URL
SN  - ISSN
N2  - Abstract or short metadata note, only when safely available
ER  -

Rules:

• Write one AU line per author.
• Use TY - JOUR for journal articles.
• End every record with ER -.
• Do not invent missing fields.
• Prefer DOI over URL when both exist.
• Keep notes concise; avoid copying long abstracts into RIS unless the source terms allow it.

EndNote import instruction

Tell the user:

In EndNote: File > Import > File, choose the `.ris` file, set Import Option to
Reference Manager (RIS), then import.

Menu labels vary slightly by EndNote version and operating system, so avoid over-specific UI claims unless the user gives their exact EndNote version.

Zotero RDF guidance

Use .rdf when the user explicitly asks for Zotero import/export.

Preferred structure:

<rdf:RDF ...>
  <bib:Article rdf:about="https://doi.org/...">
    <z:itemType>journalArticle</z:itemType>
    <dcterms:isPartOf rdf:resource="urn:..."/>
    <bib:authors>...</bib:authors>
    <dc:title>...</dc:title>
    <dc:date>YYYY-MM-DD</dc:date>
    <dc:identifier>...</dc:identifier>
    <bib:pages>...</bib:pages>
    <z:citationKey>...</z:citationKey>
  </bib:Article>
  <bib:Journal rdf:about="urn:...">...</bib:Journal>
</rdf:RDF>

Rules:

• Export one bib:Article per citation.
• Represent authors as foaf:Person nodes inside rdf:Seq.
• Deduplicate journal container nodes by journal/ISSN/volume/issue identity.
• Do not invent abstracts, attachments, or fields that are not present in metadata.

Script usage and long-article strategy

Open this reference when running scripts/nature_citation.py or when the input is long enough to need batching. It expands step 3 of the workflow.

Running the script

Start with scripts/nature_citation.py when internet access is available:

python scripts/nature_citation.py \
  --text "PASTE MANUSCRIPT TEXT HERE" \
  --scope cns \
  --outdir /tmp/nature-citation \
  --format enw \
  --with-artifacts

Useful options

• --text-file manuscript.txt: read long text from a file.
• --claim "CLAIM TEXT" or --claim-file claims.txt: treat each claim as a segment.
• --doi 10.xxxx/xxxxx or --doi-file dois.txt: export known DOI records after screening.
• --scope nature: Nature Portfolio-style journals only.
• --scope flagship: Nature, Science, and Cell only.
• --from-year 2018 --to-year 2026: constrain publication dates.
• --rows 40: raise for broad searches; keep top candidates manageable.
• --per-segment 3: number of citation candidates to keep per segment.
• --max-retries 2: retry transient Crossref failures before skipping a query.
• --format enw|ris|zotero-rdf: export format. If omitted and --output-file is set, infer from suffix.
• --mailto you@example.com: use Crossref's polite pool.
• --batch-size 10: process segments in batches of N. Each batch writes an incremental export file.
• --max-segments 20: only process the first N segments. Useful for testing or section-by-section workflows.
• --sleep 0.3: seconds between Crossref requests. Default is 0.3; raise to 1.0 if rate-limited.

Long-article strategy

When the input text is longer than roughly 3000 characters (about 10+ segments), switch to a batched workflow to avoid timeout, context overflow, or incomplete results:

1. Auto-detect length. Count segments after segmentation. If there are more than 10 segments, switch to batch mode automatically. 2. Split by section. Prefer splitting at paragraph double-line breaks or explicit section headings (Introduction, Results, etc.) so each batch is a coherent unit, not arbitrary sentence groups. 3. Process each batch independently. Run the script once per batch using --batch-size or --max-segments, OR split the text externally and call the script once per chunk. Each call writes its own intermediate export file. 4. Merge results at the end. After all batches finish, combine the intermediate files into one final export. Deduplicate by DOI. 5. Minimize inline analysis. For long articles, do NOT write detailed support-grade notes for every single segment inline. Instead:

• Write a compact summary table (segment ID → best candidate → support grade).
• Point the user to the HTML visualization for full browsing.
• Only elaborate on segments where no candidate was found or evidence is contradictory.

Quick guide

For long texts, prefer the HTML browser for review and selection instead of relying only on inline notes.

Search Strategy

Turn claims into searchable concepts

Break each sentence into:

• phenomenon: what is being claimed
• entity: gene, protein, pathway, compound, intervention, technology, population, or ecosystem
• relationship: increases, decreases, predicts, regulates, causes, associates with, improves, detects
• context: species, tissue, disease, cell type, geography, time period, device, method, or dataset
• boundary: "in cancer cells", "after treatment", "in older adults", "under drought", etc.

Create search queries at three levels:

1. precise: entity + relationship + outcome + context 2. synonym: alternate names and abbreviations 3. broad: field context if no direct paper is found

For Chinese claims, translate the scientific concepts, not the sentence literally. Keep acronyms and standard nomenclature unchanged.

Support grading

Use the smallest support grade that is defensible:

Evidence note template

Claim: [original claim]
Paper: [first author/year/title/journal/DOI]
Support grade: [grade]
Evidence basis: [title/abstract/publisher page/full text]
Reasoning: [why the result supports or does not support the exact claim]
Citation wording: [how to phrase the manuscript sentence if using this citation]

Common failure modes

• The paper is related to the same disease but tests a different mechanism.
• The paper supports an association, but the manuscript sentence claims causality.
• The evidence is in a different species, cell type, or clinical population.
• A review is used as primary evidence when original research exists.
• The claim is too broad for a single citation.
• The searched journal title contains "Nature" but is not a Nature Portfolio journal.

Better search moves

• Add the method or model when results are broad: single-cell, CRISPR screen, organoid,

randomized, cohort, meta-analysis, cryogenic electron microscopy.

• Add context terms when there are many irrelevant hits: tissue, species, cell type, disease subtype,

exposure, intervention, or outcome.

• Search the opposite direction if the claim might be overconfident: inhibits vs activates,

resistance vs sensitivity, risk vs protective.

• Use recent limits for fast-moving areas, but remove them if no direct CNS/Nature-series paper appears.

Chinese-user operating mode

When the user writes in Chinese, asks for "Nature系列", "CNS及其子刊", "支撑文献", "补引用", "自动给出引用", "分段引用", "导出EndNote", "RIS", "Zotero", "RDF", or provides Chinese manuscript text:

• Accept the text in Chinese, but search using English concept queries unless the topic is explicitly China-specific or Chinese-language scholarship.
• Return segment notes and evidence notes in Chinese by default.
• Preserve the exact source segment and translate it into one or more English search claims.
• Flag overclaiming clearly in Chinese: 强支撑, 部分支撑, 背景支撑, 不建议引用为该句支撑.
• Do not present a paper as supporting the claim merely because its title is related.

Core principles (citation)

Use this skill to turn manuscript text into a defensible citation export:

• segmented text with citation candidates for each segment
• a reference-manager import file in .enw, .ris, or Zotero .rdf
• conservative evidence notes explaining whether each candidate truly supports the segment

Default scope

Interpret journal scope from the user's wording, but keep the filter strict:

• Nature系列: search Nature Portfolio first. Include Nature, Nature [field], Nature Communications, Communications [field], Scientific Reports, and npj journals.
• CNS: search Cell, Nature, and Science plus their major sister journals.
• CNS及其子刊 or CNS/sister journals: search only accepted flagship and subjournal titles in Nature Portfolio, the AAAS Science family, and Cell Press.
• 只要Nature/Science/Cell正刊: restrict to the flagship journals Nature, Science, and Cell.

Do not treat merely related journals as in-scope. A title is valid only if it is in the accepted publisher-family whitelist or clearly matches the official naming pattern for that family. If the user needs an exhaustive or submission-critical boundary, verify current official journal pages before finalizing because journal portfolios change. The exact boundary and official source notes are in references/journal-scope.md.

Source hierarchy

Use sources in this order:

1. Structured bibliographic metadata: Crossref, PubMed/NCBI E-utilities, DOI metadata. 2. Publisher pages: nature.com, science.org, cell.com, and official journal pages. 3. Full text or abstract pages, if accessible. 4. Secondary databases such as Google Scholar, Semantic Scholar, Web of Science, or Scopus only as discovery aids, not as the sole support basis.

Prefer structured APIs for metadata and publisher pages for claim verification. If metadata and publisher page disagree, preserve the DOI and journal-page facts and flag the discrepancy.

Search quality rules

• Prefer precision over volume. A useful answer is usually 3-8 candidates, not 50 loosely related papers.
• Use exact phrase searches only for distinctive terms; otherwise use concept terms and synonyms.
• Check journal identity. Many journals contain the word "nature" but are not Nature Portfolio journals.
• Treat citation count as a tie-breaker, not evidence of support.
• Capture retractions, corrections, and expressions of concern when visible in Crossref or publisher metadata.
• Date-sensitive topics require current searching and an explicit search date.
• For medical, clinical, or safety claims, search current literature and state that citations do not replace clinical guidance or systematic review.

Source notes

This skill is based on public bibliographic APIs and official publisher/import documentation: Crossref REST API and filters, NCBI E-utilities, EndNote RIS import options, Nature Portfolio, AAAS Science journals, and Cell Press portfolio descriptions. Verify pages at use time when exact journal coverage or current import behavior matters.

Workflow

Run these seven steps for any citation job. For runs with more than ~10 segments, switch to the batched long-article strategy in references/script-usage.md.

1. Segment the text

• Split long text into citable segments. Prefer paragraph boundaries first, then sentence boundaries.
• Keep each segment focused on one citable idea when possible.
• Preserve original order and stable segment IDs such as S001, S002, S003.
• Skip obvious non-citable connective sentences unless the user asks to cite every sentence.
• For very long text, process in batches but keep a single final mapping table.

Default segmentation rules: use blank lines as paragraph boundaries; if a paragraph is longer than about 700 characters or contains multiple claims, split into sentences; merge very short fragments into neighboring text unless they contain a distinct claim; keep section headings as labels, not as citable segments. If the input has more than about 10 segments, prefer batch mode.

2. Parse each segment

For each citable segment:

• Extract the core claim in one sentence.
• Identify claim type: mechanism, association, method, clinical, epidemiology, background, definition, or review-context.
• Identify entities, intervention/exposure, outcome, population/model, directionality, and boundary.
• Convert the claim into 2-4 English search queries: one precise query with all key terms; one synonym query; one broader background query; one methods or model query if relevant.

If the claim is too broad, split it into citable subclaims rather than searching the whole sentence. For deeper help turning a claim into queries and support grades, open references/search-strategy.md.

3. Search candidate papers

Prefer scripts/nature_citation.py when internet access is available. The full flag list, polite-pool/rate-limit options, and the long-article batch strategy are in references/script-usage.md. A minimal run:

python scripts/nature_citation.py \
  --text "PASTE MANUSCRIPT TEXT HERE" \
  --scope cns \
  --outdir /tmp/nature-citation \
  --format enw \
  --with-artifacts

When the topic is biomedical or PubMed-indexed, also search PubMed with journal filters and compare results against Crossref. Use NCBI E-utilities rate limits and include tool/email parameters if running repeated searches.

4. Evaluate whether each paper supports the segment

Use a conservative support scale:

• strong support: the paper directly tests the same relationship/mechanism/method and the result supports the segment.
• partial support: the paper supports part of the segment, a related model, or a narrower condition.
• background support: the paper supports field context, not the specific claim.
• contradictory/limiting: the paper conflicts with or narrows the claim.
• metadata-only candidate: title/metadata suggest relevance, but abstract/full text has not been checked.

Never cite a metadata-only candidate as support without checking the abstract or publisher page. If a paper is a review, label it as review/context and avoid using it as primary evidence for an experimental claim when primary articles are available.

5. Export reference-manager file

Default behavior: write one reference-manager file; support publication time filters with --from-year and --to-year; for long or ambiguous texts, use --with-artifacts so the HTML browser is available.

Default file is references.enw (EndNote tagged export). Optionally references.ris (if the user requests RIS) or references.rdf (Zotero RDF). If the user asks to choose the download format, treat ENW, RIS, and Zotero RDF as the supported options and return only one export file unless they explicitly ask for multiple. Do not invent missing fields: if DOI, pages, volume, or issue are missing, leave them absent. See references/ris-endnote.md for format details.

6. Optional review artifacts

Generate review artifacts (HTML/TSV/JSON/report) for long or ambiguous runs — they are the primary way the user browses, filters, and selects candidates. Use --with-artifacts when the text is long, the query is broad, or the user needs manual curation. Report the HTML visualization path prominently when artifacts are enabled, and generate TSV/JSON/report alongside the HTML.

7. Report results

Unless the user asks for a different format, return:

交互式引用浏览器
- [absolute path to citation_visualization.html]  ← 在浏览器中打开此文件，可筛选/选择/下载引用

检索范围
- [Nature Portfolio / Science family / Cell Press / flagship only, plus date limits]

分段引用对应关系
S001: [source segment]
  - [Author, year, title, journal, DOI]
  - 支撑等级: [strong/partial/background/limiting/metadata-only]
  - 插入建议: [e.g. after sentence / after clause]

导出文件
- [absolute path to references.enw / references.ris / references.rdf]

风险和缺口
- [missing full-text check, contradictory evidence, no direct CNS literature, etc.]

Put the HTML browser path FIRST, above everything else, so the user can immediately open and browse candidates. If no suitable CNS/Nature-series paper exists, say so plainly and suggest the best nearby options from non-CNS literature only if the user wants broader coverage. If the text is long, mention the batch strategy used, especially when you limited the run with --batch-size or --max-segments.