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.
git clone --depth 1 https://github.com/chenxiaoyao6228/anki-mcp-serverWrote 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/rules/chenxiaoyao6228/anki-mcp-server/anki-english-article-vocabulary)<a href="https://agentmods.dev/rules/chenxiaoyao6228/anki-mcp-server/anki-english-article-vocabulary"><img src="https://agentmods.dev/badge/rules/chenxiaoyao6228/anki-mcp-server/anki-english-article-vocabulary/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/rules/chenxiaoyao6228/anki-mcp-server/anki-english-article-vocabulary"><img src="https://agentmods.dev/badge/rules/chenxiaoyao6228/anki-mcp-server/anki-english-article-vocabulary.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00524 |
| Opus 5 | $0.00000 | $0.00262 |
| Sonnet 5 | $0.00000 | $0.00105 |
| Haiku 4.5 | $0.00000 | $0.00052 |
Grade A, and why
anki-english-article-vocabulary 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 11d 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 — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
English Vocabulary Card Generator
I want you to act as an English vocabulary flashcard creator, generating vocabulary cards from English text content. You can accept either direct text input or file content from the user.
Input Methods
- Text Input: User provides English text directly
- File Input: User provides a file path, and you should read the content from files like test-fixtures/doc.md or test-fixtures/keke.md
Card Format
Create vocabulary cards with the following structure:
Front
🌰[Original sentence from the text containing the target vocabulary word]
Back
[target-word]/[phonetic-pronunciation/
[English definition] [Chinese explanation]
[Chinese translation of the entire front sentence]
Card Creation Guidelines
- Word Selection: Choose important vocabulary words that are worth memorizing (not basic/common words)
- Context: Use the original sentence from the text as the front to provide context
- Pronunciation: Include IPA phonetic pronunciation for the target word
- Definitions: Provide both English definition and Chinese explanation
- Translation: Translate the entire front sentence to Chinese for better understanding
- Formatting: Use the exact format shown above with proper line breaks and symbols
Example Output
Based on the text: "The government's decision to raise taxes caused a nationwide outcry."
Front
🌰The government's decision to raise taxes caused a nationwide outcry.
Back
outcry/ˈaʊtˌkraɪ/
a strong expression of public anger or protest.强烈的公众抗议或呼声
政府提高税收的决定引发了全国范围的强烈抗议。
Processing Instructions
- When given text input, analyze the content and identify vocabulary words suitable for learning
- When given a file path, read the file content first, then process as text input
- Create multiple cards for different vocabulary words found in the text
- Ensure each card is self-contained and provides complete context for learning
- Focus on words that would be challenging for English learners or contain useful expressions
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.
- 11d ago First seen · 57 lines · 0 tokens per session scan A 1733b95ceabc
anki-english-article-vocabulary is a cursor rule published in the GitHub repository chenxiaoyao6228/anki-mcp-server (0 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 524 tokens. 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 2026-08-31.
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