Efficient Local Workflows with Claude Code Hooks

Learn how to automate routine development tasks locally with Claude Code Hooks, creating fast, robust, and token-efficient workflows by combining natural language prompting with procedural code.

Claude Code Hooks Skills LLM

Overview

As a solo engineer for several early startups, I’ve built out a one-person development workflow that is both fast and robust. Part of that workflow includes custom skills I want to run every time I do a certain action - like code review every time I create a PR. With hooks, I can trigger those processes automatically, locally.

Links

https://github.com/carlymr/carlys-claude-skills
GitHub Action automating PR code reviews using Anthropic's Claude.

Tech stack

Claude Code

Anthropic's agentic coding tool: Unleash Claude's raw power directly in your terminal or IDE to turn complex, hours-long workflows into a single command.

Claude Code is Anthropic’s powerful agentic coding assistant, designed for high-velocity development. It operates natively within your terminal, IDE (VS Code, JetBrains), or via a web interface, allowing you to delegate complex tasks like feature building, bug fixing, and codebase navigation. The agent plans, edits files, executes commands, and creates commits, maintaining awareness of your entire project structure. Internally, Anthropic engineers using Claude Code reported a 67% increase in productivity, demonstrating its capacity to deliver significant gains for Pro and Max plan users.

https://claude.com/code

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Hooks

Hooks are JavaScript functions (like `useState` and `useEffect`) that let you tap into React state and lifecycle features directly from functional components, eliminating the need for class components.

React Hooks, introduced in version 16.8, are the standard for modern component logic: they allow functional components to manage state, handle side effects, and optimize performance. Core Hooks like `useState` manage local component state (e.g., a counter value), while `useEffect` handles side effects (e.g., data fetching or DOM manipulation) after a render. Custom Hooks (e.g., `useOnlineStatus`) enable logic reuse across your application, keeping components clean and focused on rendering UI.

https://react.dev/reference/react

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Skills

The essential platform for building in-demand AI and technical capabilities: access free courses, skill badges, and industry-recognized Google Cloud certifications.

Skills (Google) delivers targeted, high-impact technical training to close the global skills gap. The platform offers extensive no-cost options for all learning levels, including hundreds of courses focused on AI and technical fundamentals. Users earn shareable digital credentials: complete a certificate learning path for a full certification, or finish a series of courses to secure a Skill Badge, proving practical, technical expertise. This is the direct path for individuals and Google Cloud partners to validate knowledge and advance their careers with industry-recognized credentials.

https://skills.google

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LLM

Large Language Models (LLMs) are deep learning models, built on the Transformer architecture, that process and generate human-quality text and code at scale.

LLMs are a class of foundation models: massive, pre-trained neural networks (often with billions to trillions of parameters) that leverage the self-attention mechanism of the Transformer architecture (introduced in 2017) to predict the next token in a sequence. Trained on vast datasets (e.g., Common Crawl's 50 billion+ web pages), these models—like GPT-4, Gemini, and Claude—acquire predictive power over syntax and semantics. They function as general-purpose sequence models, enabling critical applications such as complex content generation, language translation, and automated code completion (e.g., GitHub Copilot). Their core value: generalizing across diverse tasks with minimal task-specific fine-tuning.

https://en.wikipedia.org/wiki/Large_language_model

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Efficient Local Workflows with Claude Code Hooks

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