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Coding Interview University — John Washam's CS study plan để land job tại FAANG. Data structures, algorithms, system design. Checklist-based, forked 400K+. CC BY-SA 4.0.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/yanacuti1121/Yana-AI --skill jwasham-coding-interview-university命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Sovereign-grade safety OS for AI coding agents. 62 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.
Use when the user wants to generate or keep repository documentation up to date via OpenWiki (langchain-ai/openwiki) — an LLM-driven CLI that writes a wiki for a codebase (or a personal knowledge base from Notion/Gmail/Slack/X/web search) and keeps it fresh via a scheduled CI pull request. Examples: "set up OpenWiki for this repo", "keep the docs updated automatically", "generate an agent wiki".
Use when implementing the core AR pipeline (camera pose estimation, marker tracking, projection overlay) from first principles — not when just using ARKit/ARCore/Unity's AR framework as a black box. Triggers on: 'build augmented reality from scratch', 'marker-based AR tracking', 'camera pose estimation', 'implement fiducial marker detection', 'AR projection matrix math', 'markerless AR tracking'. Covers marker-based vs markerless tracking, pose estimation, and the projection math to overlay 3D content on a camera feed.
基于 SOC 职业分类
| name | jwasham--coding-interview-university |
| description | Coding Interview University — John Washam's CS study plan để land job tại FAANG. Data structures, algorithms, system design. Checklist-based, forked 400K+. CC BY-SA 4.0. |
| allowed-tools | Read |
| user-invocable | true |
Coding Interview University: multi-month self-study curriculum của John Washam — cái anh dùng để học và đi làm tại Amazon. ~75% nội dung CS degree tập trung vào interview.
1. Prerequisites
Big-O notation, algorithmic complexity analysis
2. Data Structures
Arrays, Linked Lists, Stacks, Queues
Hash Tables, Trees (Binary, BST, AVL, B-Trees)
Heaps, Tries, Graphs
3. Algorithms
Sorting: Merge, Quick, Heap, Counting, Radix
Searching: Binary search, BFS, DFS
Dynamic Programming, Recursion, Backtracking
4. Advanced Topics
Design patterns, NP-completeness
System design (cho senior roles)
Networking fundamentals
5. Interview Prep
Resume tips, behavioral questions
Coding practice: LeetCode, HackerRank
Mock interview services
8-12h/ngày × vài tháng (John Washam's pace)
Thực tế: 3-6 tháng tùy background
1. Fork repo hoặc download ZIP
2. Mở README.md — checklist các topic
3. Tick checkbox khi hoàn thành
4. Học song song với LeetCode problems
Videos: MIT 6.006, Harvard CS50, Coursera
Books: CLRS, Cracking the Coding Interview
Practice: LeetCode, HackerRank, Pramp (mock interviews)
Design: Designing Data-Intensive Applications (Kleppmann)
https://github.com/jwasham/coding-interview-university · CC BY-SA 4.0 · +745⭐/week