
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-detailAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 552 |
|---|---|
| repo stars | ★ 811 |
| Last updated | March 13, 2026 |
| Repository | cookjohn/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
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 $ARGUMENTS contains a URL:
- Use
mcp__chrome-devtools__navigate_pagewith the URL. - Use
mcp__chrome-devtools__wait_forwith text["摘要"]and timeout 15000.
2. Check for captcha
Use mcp__chrome-devtools__take_snapshot. If "拖动下方拼图完成验证" found, notify user:
CNKI 正在显示滑块验证码。请在 Chrome 浏览器中手动完成拼图验证,完成后告诉我继续。
3. Extract paper metadata via JavaScript
Use mcp__chrome-devtools__evaluate_script with this function:
() => {
const brief = document.querySelector('.brief');
if (!brief) return { error: 'Paper detail section (.brief) not found' };
// Title
const title = brief.querySelector('h1')?.innerText?.trim()
?.replace(/\s*附视频\s*$/, '') // 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:
headinglevel 1 element - Authors:
linkelements whose URLs containkcms2/author/detail - Affiliations:
linkelements whose URLs containkcms2/organ/detail - Abstract:
StaticTextfollowing "摘要:" - Keywords:
linkelements whose URLs containkcms2/keyword/detail - Fund:
linkelements following "基金资助:" - Classification:
StaticTextfollowing "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 |
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.