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Cnki Paper Detail

  • 552 installs
  • 811 repo stars
  • Updated March 13, 2026
  • cookjohn/cnki-skills

cnki-paper-detail is a browser-automation agent skill that extracts structured CNKI academic paper metadata for developers who need citable Chinese scholarly source details in agent workflows.

About

cnki-paper-detail is an agent skill in cookjohn/cnki-skills that extracts complete bibliographic metadata from CNKI (China National Knowledge Infrastructure) paper detail pages. Given a kcms2/article/abstract URL—or an already open detail page—it uses Chrome DevTools MCP to navigate, wait for the 摘要 section, detect slider captchas, and evaluate JavaScript against the .brief DOM to return title, authors with affiliation numbers, affiliations, abstract, keywords, fund information, and CLC classification codes. Developers reach for cnki-paper-detail when building literature-review agents, comparing Chinese journal sources, or populating citation databases without manual copy-paste from CNKI. The workflow handles CNKI-specific UI quirks such as 附视频 and 网络首发 title suffixes and pauses for manual captcha completion when 拖动下方拼图完成验证 appears.

  • CNKI paper metadata extraction
  • Chinese academic source lookup
  • Citation-ready bibliographic fields
  • Abstract and detail retrieval
  • Literature review support

Cnki Paper Detail by the numbers

  • 552 all-time installs (skills.sh)
  • Ranked #370 of 1,879 Documentation skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/cookjohn/cnki-skills --skill cnki-paper-detail

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Listed on Skillselion
Installs552
repo stars811
Last updatedMarch 13, 2026
Repositorycookjohn/cnki-skills

How do you extract CNKI paper metadata automatically?

Fetch structured metadata and detail for CNKI academic papers so agents can cite, summarize, and compare Chinese scholarly sources.

Who is it for?

Developers building research agents or bibliographic pipelines that must cite CNKI Chinese academic papers with structured metadata.

Skip if: Researchers needing full PDF download, English-only databases like PubMed, or batch crawling without browser captcha handling.

When should I use this skill?

User provides a CNKI paper URL or asks for detailed metadata from a CNKI detail page already open in Chrome.

What you get

Structured JSON metadata with title, authors, affiliations, abstract, keywords, fund, and classification fields.

  • structured paper metadata JSON
  • author and affiliation lists
  • abstract and keyword arrays

By the numbers

  • Extracts 8 structured metadata fields from CNKI paper detail pages
  • Waits up to 15000 ms for 摘要 text after navigation

Files

SKILL.mdMarkdownGitHub ↗

CNKI Paper Detail Extraction

Extract complete metadata from a CNKI paper detail page.

Arguments

$ARGUMENTS is optionally a CNKI paper detail URL (containing kcms2/article/abstract). If not provided, assumes the current page is already a paper detail page.

Steps

1. Navigate to the paper page (if URL provided)

If $ARGUMENTS contains a URL:

  • Use mcp__chrome-devtools__navigate_page with the URL.
  • Use mcp__chrome-devtools__wait_for with text ["摘要"] and timeout 15000.

2. Check for captcha

Use mcp__chrome-devtools__take_snapshot. If "拖动下方拼图完成验证" found, notify user:

CNKI 正在显示滑块验证码。请在 Chrome 浏览器中手动完成拼图验证,完成后告诉我继续。

3. Extract paper metadata via JavaScript

Use mcp__chrome-devtools__evaluate_script with this function:

() => {
  const brief = document.querySelector('.brief');
  if (!brief) return { error: 'Paper detail section (.brief) not found' };

  // Title
  const title = brief.querySelector('h1')?.innerText?.trim()
    ?.replace(/\s*附视频\s*$/, '')  // remove "附视频" suffix
    ?.replace(/\s*网络首发\s*$/, ''); // remove "网络首发" suffix

  // Authors - first h3.author contains author links with sup tags
  const authorH3s = brief.querySelectorAll('h3.author');
  const authorSection = authorH3s[0];
  const authors = [];
  if (authorSection) {
    const authorLinks = authorSection.querySelectorAll('a');
    authorLinks.forEach(a => {
      const name = a.innerText?.replace(/\d+$/, '').trim();
      const supMatch = a.innerText?.match(/(\d+)$/);
      const affiliationNum = supMatch ? supMatch[1] : '';
      authors.push({ name, affiliationNum });
    });
  }

  // Affiliations - second h3.author contains org links
  const affiliations = [];
  if (authorH3s.length > 1) {
    const orgLinks = authorH3s[1].querySelectorAll('a');
    orgLinks.forEach(a => {
      affiliations.push(a.innerText?.trim());
    });
  }

  // Abstract
  const abstractEl = document.querySelector('.abstract-text');
  const abstract = abstractEl?.innerText?.trim() || '';

  // Keywords
  const keywordsP = document.querySelector('p.keywords');
  const keywords = keywordsP
    ? Array.from(keywordsP.querySelectorAll('a')).map(a => a.innerText?.replace(/;$/, '').trim())
    : [];

  // Fund
  const fundsP = document.querySelector('p.funds');
  const fund = fundsP?.innerText?.trim() || '';

  // Classification code
  const clcCode = document.querySelector('.clc-code');
  const classification = clcCode?.innerText?.trim() || '';

  // Journal/source
  const docTop = document.querySelector('.doc-top');
  const journal = docTop?.querySelector('a')?.innerText?.trim() || '';

  // Online first / publication info
  const headTime = document.querySelector('.head-time');
  const pubInfo = headTime?.innerText?.trim() || '';

  // Is online first?
  const isOnlineFirst = !!brief.querySelector('.icon-shoufa');

  // Article outline/TOC
  const catalogList = document.querySelector('.catalog-list, .catalog-listDiv');
  const toc = catalogList?.innerText?.trim() || '';

  // Citation network counts
  const citationTabs = document.querySelectorAll('ul.module-tab.tpl_lieteratures li');
  const citationInfo = {};
  citationTabs.forEach(li => {
    const id = li.getAttribute('data-id');
    const text = li.innerText?.trim();
    const countMatch = text.match(/(\d+)/);
    if (id) {
      citationInfo[id] = {
        label: text.replace(/\d+/, '').trim(),
        count: countMatch ? parseInt(countMatch[1]) : 0
      };
    }
  });

  return {
    title,
    authors,
    affiliations,
    abstract,
    keywords,
    fund,
    classification,
    journal,
    pubInfo,
    isOnlineFirst,
    toc,
    citationInfo
  };
}

4. Format and present the output

## {title} {isOnlineFirst ? "[网络首发]" : ""}

**Authors:**
{For each author: "- {name} ({affiliation})"}

**Affiliations:**
{For each affiliation: "- {affiliation}"}

**Journal:** {journal}
**Publication Info:** {pubInfo}

**Abstract:**
{abstract}

**Keywords:** {keywords joined by ", "}

**Fund:** {fund}
**Classification:** {classification}

**Citation Network:**
{For each citation type: "- {label}: {count}"}

5. Fallback: snapshot-based parsing

If JS extraction fails, use mcp__chrome-devtools__take_snapshot and parse the accessibility tree:

  • Title: heading level 1 element
  • Authors: link elements whose URLs contain kcms2/author/detail
  • Affiliations: link elements whose URLs contain kcms2/organ/detail
  • Abstract: StaticText following "摘要:"
  • Keywords: link elements whose URLs contain kcms2/keyword/detail
  • Fund: link elements following "基金资助:"
  • Classification: StaticText following "分类号:"

Verified DOM Selectors

DataSelectorNotes
Paper section.briefMain paper info container
Title.brief h1May contain icons, clean text needed
Authors.brief h3.author:first-of-type aText has superscript numbers (e.g., "张三1")
Affiliations.brief h3.author:nth-of-type(2) aText starts with "N." (e.g., "1.北京大学")
Abstract.abstract-textFull abstract text
Keywordsp.keywords aSemicolon-separated keyword links
Fundp.fundsFund information text
Classification.clc-codeCLC classification codes
Journal.doc-top aSource journal link
Online first.brief .icon-shoufaPresent if paper is online first
Citation tabsul.module-tab.tpl_lieteratures lidata-id attr identifies type

Related skills

How it compares

Use cnki-paper-detail for live CNKI detail-page DOM extraction; generic web-fetch skills cannot handle CNKI captchas or .brief-specific field parsing.

FAQ

Which CNKI fields does cnki-paper-detail extract?

cnki-paper-detail returns title, authors with affiliation numbers, institutional affiliations, abstract, keyword list, fund information, CLC classification code, and journal source data parsed from the CNKI .brief section.

What browser tools does cnki-paper-detail require?

cnki-paper-detail depends on Chrome DevTools MCP commands including navigate_page, wait_for with 摘要 text, take_snapshot for captcha detection, and evaluate_script to read DOM nodes on the CNKI detail page.

How does cnki-paper-detail handle CNKI captchas?

cnki-paper-detail snapshots the page for 拖动下方拼图完成验证 slider text, notifies the user to complete the puzzle manually in Chrome, and resumes extraction only after captcha clearance.

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