mygentic-eng

Evaluate GitHub issue quality and completeness for agent implementation

Transform rough feature ideas into comprehensive implementation specifications

Generate a new custom Claude Code slash command from a description

Generate a high-quality GitHub issue optimized for agent implementation

Complete 3-phase automation: implement → review → merge for GitHub issues

Implement multiple GitHub issues in parallel with dependency analysis

Research and plan comprehensive GitHub issues with parallel agent analysis

Research and recommend technical approaches for implementation challenges

Generate comprehensive validation command for backend or frontend

Use this agent when you need to review Python code changes with an extremely high quality bar. This agent should be invoked after implementing features, modifying existing code, or creating new Python modules. The agent applies Andre's strict Python conventions and taste preferences to ensure code meets exceptional standards. Examples: - <example> Context: The user has just implemented a new FastAPI endpoint. user: "I've added a new user registration endpoint" assistant: "I've implemented the registration endpoint. Now let me have Andre review this code to ensure it meets our quality standards." <commentary> Since new endpoint code was written, use the andre-python-reviewer agent to apply Andre's strict Python conventions and quality checks. </commentary> </example> - <example> Context: The user has refactored an existing service class. user: "Please refactor the EmailService class to handle attachments" assistant: "I've refactored the EmailService to handle attachments." <commentary> After modifying existing code, especially services, use andre-python-reviewer to ensure the changes meet Andre's high bar for code quality. </commentary> assistant: "Let me have Andre review these changes to the EmailService." </example> - <example> Context: The user has created new utility functions. user: "Create a data validation module" assistant: "I've created the data validation module." <commentary> New modules should be reviewed by andre-python-reviewer to check Pythonic patterns, type hints, and best practices. </commentary> assistant: "I'll have Andre review this module to ensure it follows our conventions." </example>

Use this agent when you need to review TypeScript code changes with an extremely high quality bar. This agent should be invoked after implementing features, modifying existing code, or creating new TypeScript components. The agent applies Andre's strict TypeScript conventions and taste preferences to ensure code meets exceptional standards. Examples: - <example> Context: The user has just implemented a new React component with hooks. user: "I've added a new UserProfile component with state management" assistant: "I've implemented the UserProfile component. Now let me have Andre review this code to ensure it meets our quality standards." <commentary> Since new component code was written, use the andre-typescript-reviewer agent to apply Andre's strict TypeScript conventions and quality checks. </commentary> </example> - <example> Context: The user has refactored an existing service module. user: "Please refactor the EmailService to handle attachments" assistant: "I've refactored the EmailService to handle attachments." <commentary> After modifying existing code, especially services, use andre-typescript-reviewer to ensure the changes meet Andre's high bar for code quality. </commentary> assistant: "Let me have Andre review these changes to the EmailService." </example> - <example> Context: The user has created new utility functions. user: "Create a validation utility for user input" assistant: "I've created the validation utility functions." <commentary> New utilities should be reviewed by andre-typescript-reviewer to check type safety, naming conventions, and TypeScript best practices. </commentary> assistant: "I'll have Andre review these utilities to ensure they follow our conventions." </example>

Use this agent when you need to research and gather external best practices, documentation, and examples for any technology, framework, or development practice. This includes finding official documentation, community standards, well-regarded examples from open source projects, and domain-specific conventions. The agent excels at synthesizing information from multiple sources to provide comprehensive guidance on how to implement features or solve problems according to industry standards. <example>Context: User wants to know the best way to structure GitHub issues for their Rails project. user: "I need to create some GitHub issues for our project. Can you research best practices for writing good issues?" assistant: "I'll use the best-practices-researcher agent to gather comprehensive information about GitHub issue best practices, including examples from successful projects and Rails-specific conventions." <commentary>Since the user is asking for research on best practices, use the best-practices-researcher agent to gather external documentation and examples.</commentary></example> <example>Context: User is implementing a new authentication system in Rails and wants to follow security best practices. user: "We're adding JWT authentication to our Rails API. What are the current best practices?" assistant: "Let me use the best-practices-researcher agent to research current JWT authentication best practices, security considerations, and Rails-specific implementation patterns." <commentary>The user needs research on best practices for a specific technology implementation, so the best-practices-researcher agent is appropriate.</commentary></example> <example>Context: User is setting up a TypeScript project and wants to know best practices. user: "What are the best practices for organizing a large TypeScript React application?" assistant: "I'll use the best-practices-researcher agent to gather comprehensive information about TypeScript React application structure, including examples from successful projects." <commentary>The user needs research on TypeScript best practices, so the best-practices-researcher agent should gather modern TypeScript conventions.</commentary></example> <example>Context: User is implementing a Python API and wants to follow best practices. user: "What are the best practices for building a FastAPI application with SQLAlchemy?" assistant: "Let me use the best-practices-researcher agent to research FastAPI and SQLAlchemy best practices, async patterns, and project structure." <commentary>The user needs research on Python-specific best practices, so the best-practices-researcher agent is appropriate.</commentary></example>

Use this agent when you need a final review pass to ensure code changes are as simple and minimal as possible. This agent should be invoked after implementation is complete but before finalizing changes, to identify opportunities for simplification, remove unnecessary complexity, and ensure adherence to YAGNI principles. Examples: <example>Context: The user has just implemented a new feature and wants to ensure it's as simple as possible. user: "I've finished implementing the user authentication system" assistant: "Great! Let me review the implementation for simplicity and minimalism using the code-simplicity-reviewer agent" <commentary>Since implementation is complete, use the code-simplicity-reviewer agent to identify simplification opportunities.</commentary></example> <example>Context: The user has written complex business logic and wants to simplify it. user: "I think this order processing logic might be overly complex" assistant: "I'll use the code-simplicity-reviewer agent to analyze the complexity and suggest simplifications" <commentary>The user is explicitly concerned about complexity, making this a perfect use case for the code-simplicity-reviewer.</commentary></example>

Use this agent when you need to conduct a comprehensive design review on front-end pull requests or general UI changes. This agent should be triggered when a PR modifying UI components, styles, or user-facing features needs review; you want to verify visual consistency, accessibility compliance, and user experience quality; you need to test responsive design across different viewports; or you want to ensure that new UI changes meet world-class design standards. The agent requires access to a live preview environment and uses Playwright for automated interaction testing. Example - "Review the design changes in PR 234"

Fast documentation verification. Checks wiki updates, README changes, and inline docs. Maximum 2 minutes. Only blocks on missing critical documentation.

Use this agent when you need to analyze and codify feedback patterns from code reviews or technical discussions to improve existing reviewer agents. Examples: <example>Context: User has provided detailed feedback on a Rails implementation and wants to capture those insights. user: 'I just gave extensive feedback on the authentication system implementation. The developer made several architectural mistakes that I want to make sure we catch in future reviews.' assistant: 'I'll use the feedback-codifier agent to analyze your review comments and update the andre-rails-reviewer with these new patterns and standards.' <commentary>Since the user wants to codify their feedback patterns, use the feedback-codifier agent to extract insights and update reviewer configurations.</commentary></example> <example>Context: After a thorough code review session with multiple improvement suggestions. user: 'That was a great review session. I provided feedback on service object patterns, test structure, and Rails conventions. Let's capture this knowledge.' assistant: 'I'll launch the feedback-codifier agent to analyze your feedback and integrate those standards into our review processes.' <commentary>The user wants to preserve and systematize their review insights, so use the feedback-codifier agent.</commentary></example>

Use this agent when you need to gather comprehensive documentation and best practices for frameworks, libraries, or dependencies in your project. This includes fetching official documentation, exploring source code, identifying version-specific constraints, and understanding implementation patterns. <example>Context: The user needs to understand how to properly implement a new feature using a Rails library. user: "I need to implement file uploads using Active Storage" assistant: "I'll use the framework-docs-researcher agent to gather comprehensive documentation about Active Storage" <commentary>Since the user needs to understand a framework/library feature, use the framework-docs-researcher agent to collect all relevant documentation and best practices.</commentary></example> <example>Context: The user is troubleshooting an issue with a Rails gem. user: "Why is the turbo-rails gem not working as expected?" assistant: "Let me use the framework-docs-researcher agent to investigate the turbo-rails documentation and source code" <commentary>The user needs to understand library behavior, so the framework-docs-researcher agent should be used to gather documentation and explore the gem's source.</commentary></example> <example>Context: The user needs to understand a TypeScript library. user: "How do I use React Query for data fetching in TypeScript?" assistant: "I'll use the framework-docs-researcher agent to gather documentation about React Query with TypeScript" <commentary>The user needs TypeScript-specific documentation for a library, so the framework-docs-researcher agent should collect type definitions and best practices.</commentary></example> <example>Context: The user needs to understand a Python library. user: "How should I use FastAPI with Pydantic models?" assistant: "Let me use the framework-docs-researcher agent to research FastAPI and Pydantic integration patterns" <commentary>The user needs Python-specific documentation, so the framework-docs-researcher agent should gather FastAPI/Pydantic best practices.</commentary></example>

Use this agent when you need to implement a specific numbered GitHub issue from any repository. The agent follows a strict 8-step workflow to create a worktree, implement the solution, run tests, and document everything comprehensively. Only invoke this agent with a single issue number. <example> Context: User wants to implement a GitHub issue from their repository user: "implement issue 5" assistant: "I'll use the issue-implementer agent to handle GitHub issue #5" <commentary> Since the user is asking to implement a specific numbered issue, use the Task tool to launch the issue-implementer agent. </commentary> </example> <example> Context: User has multiple issues to implement user: "I need to implement issues 3, 7, and 12" assistant: "I'll implement these issues one at a time. Let me start with issue #3 using the issue-implementer agent" <commentary> The agent handles one issue at a time, so launch it for issue 3 first, then separately for the others. </commentary> </example> <example> Context: User references an issue while discussing implementation user: "For issue 8, we need to add authentication to the API endpoints" assistant: "I'll use the issue-implementer agent to implement issue #8 with the authentication requirements" <commentary> When a specific issue number is mentioned with implementation intent, use the issue-implementer agent. </commentary> </example>

Use this agent when you need to merge a pull request that is ready for merge, typically after it has passed review. The agent handles the complete merge workflow including conflict resolution, status updates across all tracking systems, and cleanup. Only invoke with a single issue number at a time. <example> Context: User has an issue with a PR that passed review and needs merging. user: "Issue 5 passed review and is ready to merge" assistant: "I'll use the issue-merger agent to complete the merge process for issue 5" <commentary> Since the issue has passed review and needs merging, use the Task tool to launch the issue-merger agent. </commentary> </example> <example> Context: User wants to merge a specific PR. user: "Please merge issue 12 which has the ready_for_merge label" assistant: "I'll invoke the issue-merger agent to handle the merge for issue 12" <commentary> The user explicitly wants to merge an issue, so use the Task tool with issue-merger. </commentary> </example> <example> Context: User mentions a PR is approved and ready. user: "The PR for issue 8 is approved and all checks are passing, can you complete it?" assistant: "I'll use the issue-merger agent to merge the PR for issue 8 and update all tracking systems" <commentary> The PR is approved and ready for completion, perfect use case for the issue-merger agent. </commentary> </example>

Reviews code with a bias toward approval. Only blocks on security vulnerabilities, broken functionality, or syntax errors that prevent execution. Everything else is a suggestion that doesn't block merge.

Comprehensive quality audit with automated linting, type checking, formatting, tests, and builds. Auto-configures missing tools. Maximum 6 minutes.

Use this agent when you need to conduct thorough research on a repository's structure, documentation, and patterns. This includes analyzing architecture files, examining GitHub issues for patterns, reviewing contribution guidelines, checking for templates, and searching codebases for implementation patterns. The agent excels at gathering comprehensive information about a project's conventions and best practices. Examples: - <example> Context: User wants to understand a new repository's structure and conventions before contributing. user: "I need to understand how this project is organized and what patterns they use" assistant: "I'll use the repo-research-analyst agent to conduct a thorough analysis of the repository structure and patterns." <commentary> Since the user needs comprehensive repository research, use the repo-research-analyst agent to examine all aspects of the project. </commentary> </example> - <example> Context: User is preparing to create a GitHub issue and wants to follow project conventions. user: "Before I create this issue, can you check what format and labels this project uses?" assistant: "Let me use the repo-research-analyst agent to examine the repository's issue patterns and guidelines." <commentary> The user needs to understand issue formatting conventions, so use the repo-research-analyst agent to analyze existing issues and templates. </commentary> </example> - <example> Context: User is implementing a new feature and wants to follow existing patterns. user: "I want to add a new service object - what patterns does this codebase use?" assistant: "I'll use the repo-research-analyst agent to search for existing implementation patterns in the codebase." <commentary> Since the user needs to understand implementation patterns, use the repo-research-analyst agent to search and analyze the codebase. </commentary> </example>

Orchestrates code review by coordinating security, quality, and documentation checks. Bias toward approval - only blocks on critical issues.

Fast security-only audit. Checks for hardcoded credentials, injection vulnerabilities, and critical dependency issues. Maximum 3 minutes.

Use this agent when you need to perform security audits, vulnerability assessments, or security reviews of code. This includes checking for common security vulnerabilities, validating input handling, reviewing authentication/authorization implementations, scanning for hardcoded secrets, and ensuring OWASP compliance. <example>Context: The user wants to ensure their newly implemented API endpoints are secure before deployment. user: "I've just finished implementing the user authentication endpoints. Can you check them for security issues?" assistant: "I'll use the security-sentinel agent to perform a comprehensive security review of your authentication endpoints." <commentary>Since the user is asking for a security review of authentication code, use the security-sentinel agent to scan for vulnerabilities and ensure secure implementation.</commentary></example> <example>Context: The user is concerned about potential SQL injection vulnerabilities in their database queries. user: "I'm worried about SQL injection in our search functionality. Can you review it?" assistant: "Let me launch the security-sentinel agent to analyze your search functionality for SQL injection vulnerabilities and other security concerns." <commentary>The user explicitly wants a security review focused on SQL injection, which is a core responsibility of the security-sentinel agent.</commentary></example> <example>Context: After implementing a new feature, the user wants to ensure no sensitive data is exposed. user: "I've added the payment processing module. Please check if any sensitive data might be exposed." assistant: "I'll deploy the security-sentinel agent to scan for sensitive data exposure and other security vulnerabilities in your payment processing module." <commentary>Payment processing involves sensitive data, making this a perfect use case for the security-sentinel agent to identify potential data exposure risks.</commentary></example>