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TH

yangshun/tech-interview-handbook

Curated coding interview preparation materials for busy software engineers

142k Stars17k Forks34 Open Issues142k WatchersTypeScriptMIT
LLM ToolUI Framework
Review Readiness

This repository page has enough original analysis, source evidence, and comparison context to be treated as an indexable Git-Stars review.

100

review score

Indexable review
Decision Snapshot

Problem solved

It addresses the overwhelming and scattered nature of interview prep by condensing essential knowledge into a structured handbook. It covers not just algorithms but also non-technical aspects like resume writing and offer negotiation, filling gaps left by many other resources.

Deployment reality

The available setup signal starts with: No installation required; the content is available as a Docusaurus website and a GitHub repository. Users can read directly on the website or clone the repo for offline access.. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.

Commercial use

The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.

Capability ceiling

The handbook includes curated practice questions (Blind 75, Grind 75), algorithm cheatsheets, and step-by-step guides for behavioral interviews and resumes. It is strong on practical, condensed advice and has a large community following. Limitations: system design content is still in progress, and the repo relies on external courses for some topics, which may introduce bias.

Source and compliance noteLast synced: Aug 16, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy
Editorial Evaluation

yangshun/tech-interview-handbook is tracked as a TypeScript project in the LLM Tool, UI Framework area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.

Momentum check: the repository has 142k total stars, with +32 today, +190 this week, and +820 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.

Maintenance check: current activity is Moderate; the latest push was 68 days ago, and the open issue queue is 34, about 0.02% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.

Adoption check: 17k forks and 142k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.

Practical fit: this project is most relevant when you need TypeScript teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.

Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 820. Follow the original GitHub repository for final install, security, and release information.

Evidence Checklist

Analysis

Ready

Original problem, capability, and verdict guidance are available.

Sources

Ready

Repository metadata and README/source references are attached.

License

Ready

MIT is recorded for review.

Maintenance

Ready

Recent activity is visible in repository metadata.

Alternatives

Ready

Enough nearby projects exist for comparison.

Best For
  • TypeScript teams evaluating ecosystem-native tooling
  • teams that prefer mature projects with broad adoption signals
Avoid When
  • you need a legal review, security audit, or production SLA
Adoption Signals

Momentum

142k Stars

Reuse

17k Forks

Attention

142k Watchers

Maintenance

moderate

License

MIT

Open issues

34

Overview

Tech Interview Handbook is a free, curated set of technical interview preparation materials for busy software engineers, covering coding interviews, resume preparation, behavioral questions, and more. It has helped over 1,000,000 people and includes resources like Grind 75 and algorithm cheatsheets.

Key Features

- Best practice questions for coding interviews and Grind 75 (evolution of Blind 75) - Coding interview best practices, algorithm cheatsheets, and step-by-step resume guide - Coverage of behavioral questions and front end interview preparation

Tool Positioning

LLM Tool

Libraries and tools for LLM apps, RAG, prompts, and evals

UI Framework

Frontend frameworks, design systems, and interface libraries

Quick Start
No installation required; the content is available as a Docusaurus website and a GitHub repository. Users can read directly on the website or clone the repo for offline access.
View on GitHub Project Homepage
Project Activity

80

Health Score

Moderate

Commit Activity

Jul 5, 2016

Created

Aug 7, 2026

Last push

Source Trail

GitHub repository metadata

metadata

GitHub README

readme_summary

Star History

Star history will appear after daily syncs accumulate data.

Community Health
17k

Forks

34

Open

142k

Watchers

Owner
TH

yangshun

GitHub profile
Topics & Language
TypeScriptalgorithmalgorithm-interviewalgorithm-interview-questionsalgorithmsbehavioral-interviewscoding-interviewsinterview-practiceinterview-preparationinterview-questionssystem-design
Ecosystem & Usage
GitHub Repository Project Website Search on npm
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License
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CreatedJul 5, 2016
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Last syncedAug 16, 2026
Repository Standards

✓

License

✓

Forked

~ Moderate

Maintained