Cnki Journal Toc logo

Cnki Journal Toc

Community
cookjohn
cnki-journal-toc

Browse journal issues, view table of contents, and download original TOC PDF from CNKI. Use when user wants to see papers in a specific journal issue or download the original cover/TOC pages.

Overview

Publishercookjohn
Repositorycnki-skills
Skill namecnki-journal-toc
Stars
984
Forks
84
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cookjohn on GitHub. Read the source before you install it.

Installation

Install the Cnki Journal Toc AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cookjohn/cnki-skills/tree/master/skills/cnki-journal-toc
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cookjohn/cnki-skills.git /tmp/cnki-skills
mkdir -p .claude/skills
cp -r /tmp/cnki-skills/skills/cnki-journal-toc .claude/skills/cnki-journal-toc
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cnki Journal Toc in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cnki Journal Toc on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cnki Journal Toc is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CNKI Journal Table of Contents (期刊目录浏览 + 原版目录下载)

Browse journal issues, extract the paper list, and optionally open/download the original TOC PDF (封面+目录扫描版).

Arguments

$ARGUMENTS describes what to browse:

  • {journal name} — which journal
  • {year} (optional) — which year, defaults to latest
  • {issue} (optional) — which issue number
  • download (optional) — if included, download the original TOC PDF

Examples:

  • 计算机学报 2026 01期 — browse 2026 issue 1
  • 计算机学报 2026 01期 download — download original TOC PDF
  • 计算机学报 — shows latest (网络首发)

Steps

1. Navigate to journal detail page

If not already on a journal detail page (navi.cnki.net/knavi/detail):

  • Use cnki-journal-search to find the journal
  • Use mcp__chrome-devtools__list_pages + mcp__chrome-devtools__select_page to switch to the journal detail tab (opens in new tab)

2. Select issue + extract papers (single async evaluate_script)

Replace YEAR and ISSUE with actual values (e.g., "2025", "No.01"). The "刊期浏览" tab is the default active view — no need to click it.

javascript
async () => {
  const year = "YEAR";
  const issue = "ISSUE"; // Format: "No.01", "No.12", etc.

  const dls = document.querySelectorAll('#yearissue0 dl.s-dataList');
  let target = null;
  for (const dl of dls) {
    if (dl.querySelector('dt')?.innerText?.trim() === year) {
      target = Array.from(dl.querySelectorAll('dd a')).find(a => a.innerText.trim() === issue);
      break;
    }
  }
  if (!target) {
    // Return available years and issues for the requested year
    const available = Array.from(dls).map(dl => ({
      year: dl.querySelector('dt')?.innerText?.trim(),
      issues: Array.from(dl.querySelectorAll('dd a')).map(a => a.innerText.trim())
    })).filter(y => y.year);
    return { error: 'issue_not_found', year, issue, available: available.slice(0, 5) };
  }

  target.click();

  // Wait for paper list to load
  await new Promise((r, j) => {
    let n = 0;
    const c = () => {
      const rows = document.querySelectorAll('#CataLogContent dd.row');
      if (rows.length > 0) r();
      else if (++n > 30) j('timeout');
      else setTimeout(c, 500);
    };
    setTimeout(c, 1000);
  });

  // Extract papers
  const rows = document.querySelectorAll('#CataLogContent dd.row');
  const papers = Array.from(rows).map((dd, i) => ({
    no: i + 1,
    title: dd.querySelector('span.name a')?.innerText?.trim(),
    authors: dd.querySelector('span.author')?.innerText?.trim()?.replace(/;$/, ''),
    pages: dd.querySelector('span.company')?.innerText?.trim()
  }));

  // Get 原版目录 URL
  const tocBtn = document.querySelector('a.btn-preview:not(.btn-back)');

  return {
    issueLabel: document.querySelector('span.date-list')?.innerText?.trim(),
    paperCount: papers.length,
    papers,
    tocUrl: tocBtn?.href || null,
    url: location.href
  };
}

3. Present results

## {journal_name} — {issueLabel}

共 {paperCount} 篇论文:

1. {title}  [pp. {pages}]
   作者:{authors}

2. {title}  [pp. {pages}]
   作者:{authors}
...

4. Download original TOC PDF (if requested)

If user requested download, or asks for "原版目录":

Method A — Click "原版目录浏览" to open reader, then download:

  1. Find the link with text "原版目录浏览" in the snapshot (class btn-preview)
  2. Click it — this opens a new tab with the reader page (kns.cnki.net/reader/report)
  3. Use mcp__chrome-devtools__list_pages to find the new reader tab
  4. Use mcp__chrome-devtools__select_page to switch to it
  5. Use mcp__chrome-devtools__wait_for with text ["下载"]
  6. Take snapshot — find the link with text "下载" (the download button in the reader toolbar)
  7. Click the download link — triggers PDF download via Chrome

Method B — Direct download from reader page:

If already on a reader page (kns.cnki.net/reader/report):

  1. Take snapshot
  2. Find link with text "下载"
  3. Click it

After clicking, inform the user:

原版目录 PDF 下载已触发,请在 Chrome 下载管理器中查看。

Tool calls

  • Browse issue: 1 (evaluate_script only) — after navigating to journal page
  • Download TOC: requires snapshot + click + tab switching (new tab)

Verified selectors

Journal Detail — 刊期浏览

ElementSelectorNotes
刊期浏览 taba text "刊期浏览"default active (li.on.cur), no need to click
Year area#yearissue0 / .yearissuepage
Year groupsdl.s-dataListinside #yearissue0
Year labeldl.s-dataList dttext "2026", "2025" etc.
Issue linksdl.s-dataList dd atext "No.01", "No.12" etc.
Issue labelspan.date-listtext "2025年01期"
Paper container#CataLogContent
Paper entries#CataLogContent dd.row
Paper titledd.row span.name ahref to kcms2/article/abstract
Paper authorsdd.row span.authorsemicolon-separated
Paper page rangedd.row span.companyclass is "company" but holds page range
Paper IDdd.row b[name="encrypt"]id like "JSJX202512001"
原版目录浏览a.btn-preview:not(.btn-back)href to bar.cnki.net/bar/download/order
返回a.btn-preview.btn-back

Reader Page (kns.cnki.net/reader/report)

ElementPattern
Page titleRootWebArea "期刊原版目录"
Download buttonlink text "下载", URL to bar.cnki.net/bar/download/order
Current pagetextbox value (page number)
Total pagesStaticText (e.g., "4")
Navigationgeneric description "上一页" / "下一页"

Important Notes

  • "原版目录浏览" only appears when a specific issue is selected (not for 网络首发 view).
  • The reader page opens in a new tab.
  • The download link in the reader requires login. If download fails, remind user to log in.
  • The download URL is session-specific — do not cache or reuse.

Frequently asked questions

What does the Cnki Journal Toc AI skill do?

Browse journal issues, view table of contents, and download original TOC PDF from CNKI. Use when user wants to see papers in a specific journal issue or download the original cover/TOC pages.

Why use Cnki Journal Toc on TypingMind?

Because you install it once and use it with any model. Cnki Journal Toc is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cnki Journal Toc in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cookjohn/cnki-skills/tree/master/skills/cnki-journal-toc. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cnki Journal Toc?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cnki Journal Toc?

As many as you like. As long as a model supports skills, you can use Cnki Journal Toc with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cnki Journal Toc AI skill free?

It is published on GitHub by cookjohn. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇