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Cnki Paper Detail skill

Extract full paper details from a CNKI paper page including title, authors, affiliations, abstract, keywords, fund, classification. Use when the user needs detailed information about a specific paper.

$npx skills add cookjohn/cnki-skills --skill cnki-paper-detail
View this skill on GitHubcookjohn/cnki-skills/skills/cnki-paper-detail/SKILL.md
Pack stars
1,059
Pack installs
6.1k
Alyn Score
47/99
Updated
8 months ago
– views – installs via Alyn

Install Cnki Paper Detail

Pick your agent. Every command is ready to paste.

$npx skills add cookjohn/cnki-skills --skill cnki-paper-detail

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads cnki-paper-detail when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the cnki-paper-detail skill”. In Codex, type $cnki-paper-detail.

The skill itself

SKILL.md

FolderGitHub

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

Data Selector Notes
Paper section .brief Main paper info container
Title .brief h1 May contain icons, clean text needed
Authors .brief h3.author:first-of-type a Text has superscript numbers (e.g., "张三1")
Affiliations .brief h3.author:nth-of-type(2) a Text starts with "N." (e.g., "1.北京大学")
Abstract .abstract-text Full abstract text
Keywords p.keywords a Semicolon-separated keyword links
Fund p.funds Fund information text
Classification .clc-code CLC classification codes
Journal .doc-top a Source journal link
Online first .brief .icon-shoufa Present if paper is online first
Citation tabs ul.module-tab.tpl_lieteratures li data-id attr identifies type

Tips for Cnki Paper Detail

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • It is part of a pack with 10 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Cnki Paper Detail

What does the Cnki Paper Detail skill do?

Extract full paper details from a CNKI paper page including title, authors, affiliations, abstract, keywords, fund, classification. Use when the user needs detailed information about a specific paper.

How do I install Cnki Paper Detail?

Run "npx skills add cookjohn/cnki-skills --skill cnki-paper-detail" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Cnki Paper Detail work in Cursor and Codex?

Yes. Cnki Paper Detail uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Cnki Paper Detail free?

Cnki Paper Detail is open source on GitHub. It is free to install; check the license before commercial use.

Who made Cnki Paper Detail?

Cnki Paper Detail is published by cookjohn in the cookjohn/cnki-skills repository, together with 9 other skills.

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