Skill flagged — suspicious patterns detected

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Adaptive Learning

v1.0.0

Create adaptive learning flashcard apps from course materials (URLs, PDFs, or folders). Uses FSRS (Free Spaced Repetition Scheduler) and Bayesian Knowledge T...

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byTree@weishuz
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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high confidence
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Purpose & Capability
Name/description match the included frontend framework, FSRS library, and course-bundling script. However, the SKILL.md instructs the agent to fetch course pages and download PDFs to ~/COURSE_NAME/ and to read local folders — actions for which no scraping/parsing code or CLI tools are provided. The provided artifacts only support bundling an existing questions.json into a browser app; they do not implement automated web scraping or PDF extraction.
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Instruction Scope
SKILL.md tells the agent to 'Fetch the course page, extract topic list and resource links' and 'Download HW/Discussion/Lecture PDFs to ~/COURSE_NAME/'. The runtime code is a client-side app plus a packaging script that expects a questions.json; there are no instructions or tools in the package to perform web requests, parse HTML, or extract PDFs. This is scope creep: the instructions ask for filesystem/network actions beyond what the shipped files perform. If an agent attempted to follow those instructions it would need extra network and filesystem privileges not described by the skill.
Install Mechanism
No install spec (instruction-only / static files) — low friction. The frontend references KaTeX from jsDelivr (CDN). The included generate-course.sh writes a preload script by inlining the questions.json directly into a JS file (no JSON escaping), and uses sed -i which can behave differently across platforms. These are not outright malicious but are implementation details to review before running.
Credentials
Skill declares no required environment variables, no external credentials, and no config paths. That matches the included files (pure frontend + packaging script).
Persistence & Privilege
always:false and default autonomy. The skill does persist course state to localStorage within the browser (alearn_ prefix) which is expected for a client-side learning app. It does not request elevated or cross-skill privileges.
What to consider before installing
This package contains a browser-based flashcard framework and a shell script to bundle an existing questions.json into a course — that part is coherent and appears benign. However, SKILL.md also tells the agent to fetch webpages and download PDFs and to read local folders; the shipped code does not implement scraping or PDF parsing. Before installing or running anything: - Do not grant an agent automatic filesystem or network access to run those undocumented scraping/download steps. The instructions expect capabilities (web scraping, writing to ~/COURSE_NAME/) that aren't present in the code. - If you plan to run scripts locally, inspect scripts/generate-course.sh and the generated preload-<id>.js. The script inlines your questions.json into a JS file without escaping — malformed or malicious JSON could break the generated JS or lead to unexpected behavior. Only run the script with questions.json you trust, and review the resulting preload JS before opening it in a browser. - The frontend loads KaTeX from jsDelivr; if you require offline or audited dependencies, host these libraries yourself. - If you need automatic scraping/PDF extraction, request or provide explicit scraper/parsing code (or a vetted tool) rather than relying on the SKILL.md prose. The current mismatch (instructions vs. implementation) is why this skill is flagged suspicious — it may be incomplete or expect external, unstated capabilities. Additional information that would change this assessment: any included or referenced, auditable scraper/parser tools, or clear statement that the agent will not autonomously attempt filesystem/network actions beyond bundling a provided questions.json.

Like a lobster shell, security has layers — review code before you run it.

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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

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