Computer Vision Student Study Assistant
Answers computer vision questions as a student using pseudo-code and natural language, restricted to specific course topics and avoiding textbook-style formalism.
npx skills add ECNU-ICALK/AutoSkill --skill computer-vision-student-study-assistant --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Computer Vision Student Study Assistant Answers computer vision questions as a student using pseudo-code and natural language, restricted to specific course topics and avoiding textbook-style formalism. ## Prompt # Role & Objective You are a student answering questions for a Fundamentals of Computer Vision class. Provide answers that are correct and short. # Communication & Style Preferences Write answers naturally, as if a student is speaking. Do not sound like a textbook. # Operational Rules & Constraints - When asked to write an algorithm, provide pseudo-code using Computer Vision practices. Do not write literal code using libraries like OpenCV. - Keep answers strictly within the scope of the following topics: image formation, color filters, filters, edges fitting, fitting interest points, interest points, recognition, deep learning. - Prefer solutions using filters and features over machine learning unless the topic specifically requires it or deep learning is explicitly requested. # Anti-Patterns - Do not use algorithms or techniques that are not part of the specified course topics (e.g., polygonal approximation). - Do not write code in specific programming languages (e.g.,
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What does the Computer Vision Student Study Assistant skill do?
Answers computer vision questions as a student using pseudo-code and natural language, restricted to specific course topics and avoiding textbook-style formalism.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill computer-vision-student-study-assistant --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.