Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add YuanyuanMa03/academic-research-skills --skill cnki-parse-resultsgit clone --depth 1 https://github.com/YuanyuanMa03/academic-research-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/cnki-parse-results)<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/cnki-parse-results"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/cnki-parse-results/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/cnki-parse-results"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/cnki-parse-results.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00043 | $0.01153 |
| Opus 5 | $0.00022 | $0.00576 |
| Sonnet 5 | $0.00009 | $0.00231 |
| Haiku 4.5 | $0.00004 | $0.00115 |
Grade A, and why
cnki-parse-results scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CNKI Parse Search Results
Extract structured paper data from the current CNKI search results page.
Prerequisites
The current Chrome page must be a CNKI search results page (URL contains kns.cnki.net and page shows "条结果").
Steps
1. Verify we are on a results page
Use mcp__chrome-devtools__take_snapshot. Verify the page contains "条结果". If not, inform the user that no search results page is currently open.
Check for captcha ("拖动下方拼图完成验证") - if found, notify user to solve it manually.
2. Extract results via JavaScript
Use mcp__chrome-devtools__evaluate_script with this function:
() => {
const rows = document.querySelectorAll('.result-table-list tbody tr');
const checkboxes = document.querySelectorAll('.result-table-list tbody input.cbItem');
const results = Array.from(rows).map((row, index) => {
const nameCell = row.querySelector('td.name');
const titleLink = nameCell?.querySelector('a.fz14');
const authorCell = row.querySelector('td.author');
const sourceCell = row.querySelector('td.source');
const dateCell = row.querySelector('td.date');
const dataCell = row.querySelector('td.data');
const quoteCell = row.querySelector('td.quote');
const downloadCell = row.querySelector('td.download');
const isOnlineFirst = !!nameCell?.querySelector('.marktip');
return {
number: index + 1,
title: titleLink?.innerText?.trim() || '',
url: titleLink?.href || '',
exportId: checkboxes[index]?.value || '',
authors: Array.from(authorCell?.querySelectorAll('a.KnowledgeNetLink') || []).map(a => a.innerText?.trim()),
journal: sourceCell?.querySelector('a')?.innerText?.trim() || '',
date: dateCell?.innerText?.trim() || '',
database: dataCell?.innerText?.trim() || '',
citations: quoteCell?.innerText?.trim() || '',
downloads: downloadCell?.innerText?.trim() || '',
isOnlineFirst: isOnlineFirst
};
});
const totalText = document.querySelector('.pagerTitleCell')?.innerText || '';
const totalMatch = totalText.match(/([\d,]+)/);
const pageInfo = document.querySelector('.countPageMark')?.innerText || '';
return {
papers: results,
totalCount: totalMatch ? totalMatch[1] : 'unknown',
pageInfo: pageInfo
};
}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 111 lines · 43 tokens per session scan A ffabd3e3ab48
cnki-parse-results is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (63 stars, last pushed 22d ago), licensed MIT. It adds 43 tokens to every session and 1,153 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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