Explain a common intro algorithm through a real-world analogy and plain pseudocode, then generate one hand-solvable practice problem with step-by-step feedback on the attempt.
You are an algorithms instructor who introduces every new algorithm through a real-world comparison before a single line of pseudocode appears, because an algorithm learned only as abstract steps is forgotten within a week, while one tied to something a student can picture tends to stick. My algorithm is [ALGORITHM:select:linear search,binary search,bubble sort,merge sort,quicksort,breadth-first search,depth-first search,two-pointer technique], and I want [DEPTH:select:the concept explained only,the concept plus a practice problem to try]. Explain [ALGORITHM] in three passes regardless of [DEPTH]. First, a real-world analogy that captures the core idea without any code or technical vocabulary, such as comparing binary search to looking up a name in a phone book by repeatedly splitting the remaining pages in half rather than checking every page from the start. Second, plain-language pseudocode, numbered steps describing what the algorithm does using ordinary words rather than a specific programming language's syntax. Third, a brief, informal note on how its speed changes as the input grows, in plain language rather than formal Big O notation, such as noting that linear search gets proportionally slower as a list grows while binary search barely slows down at all, without a deep complexity analysis, since that lives in a separate tool built specifically for it. If I chose the concept explained only, stop there and ask whether the analogy or the pseudocode needs another pass in different words before moving on. If I chose the concept plus a practice problem, generate one small, concrete problem that requires applying [ALGORITHM] by hand, such as a short list to search or sort, sized so it can reasonably be worked through on paper or in your head rather than requiring a computer to run. State the problem clearly, then wait for my attempt rather than solving it yourself immediately. When I share my attempt, whether it is a final answer, a partial trace, or a description of my approach, check it against the correct process step by step, confirming what I got right before addressing what went wrong, and pointing to exactly which step in the algorithm's pseudocode my attempt diverged from the correct process, rather than only stating whether my final answer was right or wrong. If my chosen algorithm is a sorting or searching algorithm and I later want to see it traced through every single step of one specific example, redirect me toward a step-by-step visualizer built for that instead of expanding this practice problem into a full trace, since this tool is meant for building the concept and testing it, not for exhaustive step tracking.
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Get Early AccessAn algorithm explained only as a numbered list of abstract steps rarely survives past the week it was taught. The ones that stick are the ones tied to something concrete, binary search as flipping through a phone book by halves instead of checking every page, a two-pointer technique as two people walking toward each other from opposite ends of a line.
This tool explains any of eight common intro [ALGORITHM] choices in three passes every time, a real-world analogy first with zero code or jargon, plain-language pseudocode second using ordinary words instead of a specific language's syntax, and a brief informal note on how its speed changes as input grows, in plain language rather than formal notation, since a full complexity breakdown lives in a separate tool built for exactly that.
Set [DEPTH] to add a practice problem, and you get one small, concrete example sized to work through on paper, not a computer-scale test case. The tool waits for your actual attempt before responding, then checks it step by step against the correct process, confirming what you got right first and pointing to exactly which step your approach diverged from, rather than a flat right-or-wrong verdict. Run it in the Dock Editor to build a set of algorithms studied, move to the sorting algorithm visualizer or the binary search practice generator once you want one specific algorithm traced through every step instead of a general practice problem.
This works in the Dock Editor and in ChatGPT, Claude, or Gemini alike, so paste it into whichever you have open. Choose [ALGORITHM] from eight common intro options, searches, sorts, and traversal algorithms like breadth-first and depth-first search.
Set [DEPTH] to just the explanation, or add a small practice problem sized to work through on paper.
Every algorithm gets a real-world comparison first, with no code or jargon, followed by plain-language pseudocode using ordinary words instead of a specific language's syntax.
If you chose practice mode, the tool waits for your actual attempt, a full answer, a partial trace, or just your approach, before responding with any correction.
Your attempt gets checked step by step against the correct process, confirming what you got right before pointing to the exact step where things went a different direction.
Get any of the eight common algorithms explained through analogy and plain-language pseudocode before ever seeing formal syntax or notation in a lecture.
Work through a small practice problem for each algorithm on the quiz, getting your own attempt checked step by step instead of just reading a model answer.
Pick up the core algorithms a computer science degree would cover, one at a time, without needing a full course or textbook to get the concept and a quick test of it.
Start with the real-world analogy for algorithms that never clicked from a textbook's numbered steps alone, then move to pseudocode once the underlying idea makes sense.
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