1. Software Development

Enforces Test-Driven Development by requiring tests to be written before implementation code.

Automates the end-to-end creation of functional code from initial user concepts without manual coding.

Automates generation and execution of Jest unit tests for incremental code changes in VChart, comparing against a base branch and providing coverage reports.

Creates a new Git branch in VChart with topic-based naming, based on a specified base branch (default: develop).

Reviews pull requests against comprehensive guidelines including security, correctness, clean code, and accessibility.

Generates comprehensive testing plans by analyzing code changes in branches or PRs, supporting QA checklist creation and PR readiness verification.

A Rust fuzzing tool for testing code with libFuzzer, integrated with Cargo for Rust projects.

Expert analysis of DWARF debug format (v3-v5) for interpreting debug information in compiled code.

Guides implementation of property-based testing for code validation, serialization, and feature design across multiple languages and smart contracts.

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

Creates language variants of Semgrep rules for multi-language codebase security scanning and analysis.

Provides on-demand access to specific sections of official Claude Code documentation for accurate implementation of hooks, skills, and MCP servers.

Compares z.ai GLM 4.7 and code-searcher responses to provide dual-AI perspectives on code analysis and questions.

Guides porting R's bslib UI components to py-shiny, covering source analysis, Python implementation, asset vendoring, testing, and documentation.

Provides guidelines for writing and maintaining unit tests in the S2 project to ensure proper code coverage during source code modifications.

Runs S2 project code linting to catch errors before git push, ensuring code quality and avoiding commit failures.

Automated code review for pull requests, checking quality, security, and best practices.

Removes unnecessary or redundant code generated by AI assistants, improving code clarity and maintainability.

Provides Vercel-engineered performance optimization guidelines for React and Next.js applications, covering components, data fetching, and bundle efficiency.

An iterative agent that identifies root causes, implements fixes, and validates solutions through evidence gathering and testing until the issue is resolved.

Enforces systematic root cause investigation before implementing fixes for bugs, test failures, or unexpected behavior.

Manages isolated Git worktrees for parallel development, eliminating branch switching and streamlining workspace cleanup after PR merges.

Generates clear and descriptive commit messages from git diffs to improve version control communication and code review efficiency.

Explains plugin lifecycle, generator types, and utilities for developing plugins within the Kubb code generation ecosystem.