AI-powered learning coach that accelerates mastery through spaced repetition, personalized syllabi, and active practice.
Built for Claude Code - Integrates AI coaching directly into your development environment.
Also supports Codex with agent-specific AGENTS.md instructions and shared learning tools. Codex support is less strict than Claude Code because Codex does not currently expose a CLI flag for replacing the system prompt; Learn FASTER can only inject coaching behavior through AGENTS.md, startup prompts, or future skill-style instructions. Codex also only exposes its structured user-input tool in Plan mode, so in Default mode it cannot present guided choice prompts the same way Claude Code can.
Master any technical skill with science-backed learning principles:
- Personalized syllabi generated for your skill level and learning goals
- Spaced repetition system that schedules reviews at optimal intervals
- Four learning modes - choose Balanced, Exam-Prep, Theory-Focused, or Practical
- Active practice with auto-generated exercises and projects
- Progress tracking to visualize your learning journey
- Forget: Beginner's mindset - approach topics with fresh perspective
- Act: Learn by doing - hands-on practice over passive reading
- State: Optimize focus - create ideal learning conditions
- Teach: Explain to retain - teaching reinforces understanding
- Enter: Consistent sessions - regular practice builds momentum
- Review: Spaced repetition - review at intervals for long-term retention
Prerequisites: uv package manager
# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | shInstall once and use across all projects:
uv tool install learn-faster --from git+https://github.com/cheukyin175/learn-faster-kit.gitThen in any project directory, simply run:
learn-fasterThis will auto-initialize on first run and launch Claude Code with FASTER coaching mode.
Run directly without installation:
uvx --from git+https://github.com/cheukyin175/learn-faster-kit.git learn-fasterOn first run, learn-faster creates shared learning tools plus agent-specific instructions.
For Claude Code:
your-project/
├── .claude/
│ ├── agents/practice-creator.md
│ ├── commands/
│ │ ├── learn.md
│ │ ├── review.md
│ │ └── progress.md
│ └── settings.local.json
├── .learning/
│ ├── config.json (tracks initialization)
│ ├── scripts/
│ │ ├── init_learning.py
│ │ ├── log_progress.py
│ │ ├── review_scheduler.py
│ │ └── generate_syllabus.py
│ └── references/faster_framework.md
└── CLAUDE.md
For Codex, run learn-faster init --agent codex. It creates the same .learning/ shared tools and writes Codex instructions to AGENTS.md. Because Codex does not provide a system-prompt replacement flag, adherence depends on Codex reading those project instructions and the launch prompt. Codex guided-choice interactions are also limited: the user-input tool is available only in Plan mode, so Default mode falls back to plain conversational questions.
-
Install the tool
uv tool install learn-faster --from git+https://github.com/cheukyin175/learn-faster-kit.git
-
Launch in any project directory
cd your-learning-project learn-fasterFirst run will:
- Prompt you to select a learning mode
- Initialize the project structure
- Launch your configured agent with FASTER coaching enabled
-
Start learning
/learn "Golang fundamentals"The AI coach will generate a personalized syllabus and guide your learning session.
The "T" in FASTER—teaching to retain—is the key differentiator. Here's how it works:
mkdir learn-go && cd learn-go
learn-faster # Select "Balanced" mode
/learn "Go error handling" # In Claude CodeCoach: You've just learned about error wrapping. Ready to teach it back?
┌ Teach Back
│ ● Yes, let me explain
│ ○ Need review first
│ ○ Not sure yet
└
You: So when you wrap an error with fmt.Errorf and %w, you're adding
context like "failed to open config" while keeping the original
error inside. Then errors.Is can still match the root cause.
Coach: ✅ Great explanation! You nailed the key insight—wrapped errors
preserve the chain for inspection. Adding "error wrapping" to
your review schedule. First review tomorrow.
Why this works: Explaining concepts in your own words forces active recall—proven to boost retention 2-3x vs passive reading. The coach won't just tell you answers; it guides you to construct understanding yourself.
learn-faster- Launch Claude Code with FASTER coaching (auto-initializes on first run)learn-faster init- Force re-initialization or switch learning modeslearn-faster init --agent codex- Initialize the project for Codex instead of Claude Codelearn-faster resume [<id>] [--pick] [--fork]- Resume a previous coaching session (--pickto choose interactively;--forkto branch into a new session id)learn-faster version- Show current version
Once Claude Code is running, use these commands:
/learn [topic]- Start or continue learning a topic with personalized syllabus/review- Spaced repetition review session for topics you've learned/progress- View detailed progress report and learning statistics
Choose the mode that fits your learning style:
- Balanced - Mix of theory, practice, and real-world application (recommended for most learners)
- Exam-Prep - Focused on recall, practice tests, and certification preparation
- Theory-Focused - Deep conceptual understanding with mental models and first principles
- Practical - Project-based learning with immediate application
Each mode provides a tailored coaching experience with mode-specific syllabi and exercises.
# Clone the repository
git clone https://github.com/cheukyin175/learn-faster-kit.git
cd learn-faster-kit
# Install uv if needed
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install dependencies
uv syncLearn FASTER is ideal for:
- Learning new programming languages (Go, Rust, Python, TypeScript, etc.)
- Preparing for technical certifications and exams
- Mastering frameworks and libraries (React, Next.js, Django, etc.)
- Building structured self-study programs
- Onboarding to new codebases or technologies
- Python 3.12+
- Claude Code
- uv package manager
Contributions are welcome! Feel free to open issues or submit pull requests.
MIT License - See LICENSE file for details