1. Software Development

Provides automated testing and validation utilities for software components and code.

Requires execution of verification commands and confirmation of output before claiming code completion, preventing premature success assertions in development.

Provides consistent Python code style patterns including modern type hints, import organization, and docstring conventions for clean, maintainable code.

Creates isolated Git worktrees for feature development with smart directory selection and safety verification.

Gemini-based coding assistant for generating code, debugging errors, translating programming languages, and explaining complex logic.

Provides best practices for defining MCP tools using JSON schemas, including inputSchema, outputSchema, and annotations to guide model behavior.

Critically evaluates code review feedback for technical accuracy and clarity before implementation, ensuring rigorous verification over passive acceptance.

Reviews test design quality for agentic code, ensuring test type appropriateness, ADR compliance, and Constitution alignment before PR.

Enables parallel execution of independent tasks without shared state, improving application efficiency and resource utilization.

Guides developers through final branch integration steps, offering structured options for merging, pull requests, and cleanup after successful implementation and testing.

Enforces consistent Python code quality through pre-commit linting, type checking, complexity analysis, and test execution in fast or comprehensive modes.

Executes pytest to validate test results and code coverage, ensuring code changes don't break existing functionality.

Enforces consistent Python code style with modern type hints, clean structure, and best practices for readability and maintainability.

Guides developers through final branch integration steps, offering structured options for merging, pull requests, or cleanup after successful implementation and testing.

Provides a structured methodology to diagnose and resolve software bugs, test failures, and unexpected behavior before implementing solutions.

Provides a structured methodology for identifying and resolving software bugs, test failures, and unexpected behavior before implementing solutions.

Clarifies ambiguous requirements before implementation to prevent misalignment and ensure accurate development.

Enables fullstack development for WL Backoffice system, supporting frontend (Kirby), backend API (Coloris), and database (SQL) implementation.

Automates software implementation by delegating tasks to subagents with dual review for specification adherence and code quality, ensuring efficient development.

Requires running verification commands and validating output before claiming code completion, ensuring evidence precedes assertions in development workflows.

Enables writing tests before implementation code for features and bug fixes, ensuring quality and design.

Enables creation, editing, and verification of AI skills before deployment.

Creates production-ready MCP servers via MCP SDK, handling scaffolding, configuration, security, and deployment with best practices for Claude Code integration.

Facilitates peer code review requests to verify code quality, standards compliance, and requirement fulfillment before merging into main branches.