claude

algo-sensei

Personal DSA & LeetCode mentor skill: explanations, progressive hints, code review, mock interviews, pattern recognition.

2 on GitHubby karanb192v1.0.0MITupdated 3 days ago
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Plugin algo-sensei from marketplace kushal-claude-plugins in Kushal9889/claude-plugins. Commands read from the repo's manifest — 2 days ago.

What it installs

Skills (6)

  • algo-sensei-hint

    DSA progressive-hint mode (Socratic) - guides toward solution via 5-level hints without spoiling the answer. Trigger on "give me a hint", "I'm stuck", "guidance" on a problem, "don't tell me the answer", "progressive hints", "let me figure it out myself".

  • algo-sensei-interview

    DSA mock-interview mode - roleplays a FAANG technical interviewer (problem presentation, hints, evaluation rubric, feedback). Trigger on "mock interview", "practice interview", "be the interviewer", "interview simulation", or wanting to practice explaining solutions verbally under pressure.

  • algo-sensei-pattern-mapper

    DSA pattern-recognition mode - teaches HOW to identify algorithmic patterns from problem characteristics and signal keywords (Two Pointers, DP, Sliding Window, Graphs, etc). Trigger on "what pattern is this?", "I can't figure out the approach", "similar problems", "which technique to use", or proble

  • algo-sensei-review

    DSA code review mode - correctness, complexity, code quality, optimization, edge cases, interview-readiness feedback. Trigger when user shares code and asks "review", "feedback", "is this optimal?", "can I improve this?", "what's wrong with my solution?", or wants complexity analysis / optimization

  • algo-sensei-tutor

    DSA tutor mode - explains concepts/problems with structured teaching, examples, ASCII diagrams, pattern intuition. Trigger on "explain", "I don't understand", "teach me", "help me learn", "what is X", "how does X work", or beginner-level DSA questions.

  • algo-sensei

    Your personal DSA & LeetCode mentor. Use for problem explanations, progressive hints, code reviews, mock interviews, pattern recognition, complexity analysis, and custom problem generation. Automatically adapts to your learning style and request type.

View source on GitHub

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