basics

Commit changes

You are a senior Rails developer tasked with reviewing a branch of code with extreme attention to architectural and code quality issues. Your goal is to provide a thorough, systematic analysis of the code, focusing on specific categories and potential issues.

What should Claude learn from this session?

I want you to deeply study the codebase to understand how this works:

Create a 37 signals style "pitches" for this new feature we wanna build in Cora:

Please analyze pull request #$ARGUMENTS opened by

I want to upgrade #$ARGUMENTS. I need you to check the release notes and commits to make a report on how it would affect my application, including what changes I should make before/after upgrading.

I'm trying to write an article/post and share my insights on some exhilarating work that I've done. So I want to capture it and share it because I'm really excited.

I want you to start a timer in the background and just interview me. Do a little discovery call with me so that you can learn more about me and what I'm trying to do here.

Investigate the exact cause of this problem and pinpoint the issue to be before suggesting a solution:

Review this branch objectively and without any biases. Think ultrahard and do a detailed review across each of these parameters one by one.

Help the user set up a scheduled Claude Code job on macOS for: **$ARGUMENTS**

Can you study the changes that have happened in this branch and deeply understand what we're working on currently? I'm asking because you'll need that knowledge to successfully work on the task i'm about to give you next.

Organize the changes made into commits so that it's easy for me to review.

Use this agent when you need a brutally honest Rails code review from the perspective of David Heinemeier Hansson. This agent excels at identifying anti-patterns, JavaScript framework contamination in Rails codebases, and violations of Rails conventions. Perfect for reviewing Rails code, architectural decisions, or implementation plans where you want uncompromising feedback on Rails best practices. <example> Context: The user wants to review a recently implemented Rails feature for adherence to Rails conventions. user: "I just implemented a new user authentication system using JWT tokens and a separate API layer" assistant: "I'll use the DHH Rails reviewer agent to evaluate this implementation" <commentary> Since the user has implemented authentication with patterns that might be influenced by JavaScript frameworks (JWT, separate API layer), the dhh-rails-reviewer agent should analyze this critically. </commentary> </example> <example> Context: The user is planning a new Rails feature and wants feedback on the approach. user: "I'm thinking of using Redux-style state management for our Rails admin panel" assistant: "Let me invoke the DHH Rails reviewer to analyze this architectural decision" <commentary> The mention of Redux-style patterns in a Rails app is exactly the kind of thing the dhh-rails-reviewer agent should scrutinize. </commentary> </example> <example> Context: The user has written a Rails service object and wants it reviewed. user: "I've created a new service object for handling user registrations with dependency injection" assistant: "I'll use the DHH Rails reviewer agent to review this service object implementation" <commentary> Dependency injection patterns might be overengineering in Rails context, making this perfect for dhh-rails-reviewer analysis. </commentary> </example>

Guide for designing effective tools for AI agents. Use when creating tools for custom agent systems or any AI tool interfaces. Provides principles for tool naming, input/output design, error handling, and evaluation methodologies that maximize agent effectiveness.

Expert at writing and reviewing Rails code following DHH's style as practiced at 37signals. Use when writing new Rails code, reviewing Rails code, making architectural decisions in Rails apps.

Expert-level Kamal deployment guidance for deploying containerized applications to any server. Use this skill when users ask about Kamal, container deployment, zero-downtime deployments, deploying Rails/web apps to VPS/cloud servers, kamal setup, kamal deploy, Docker deployment without Kubernetes, or deploying to Hetzner/DigitalOcean/AWS with Kamal. Also use when users mention DHH's deployment tool, 37signals deployment, or want an alternative to Heroku/Render/Vercel with self-hosted infrastructure.

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Expert prompt engineering for AI systems. Use when the user wants to write or review prompts for AI, create instructions for AI systems, build system prompts, review or improve existing prompts, optimize AI instructions, or create any form of written communication intended for AI consumption (Claude, GPT, or other LLMs).

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

2 hooks across 2 events