Skill UI

This comprehensive skill provides best practices for secure coding across multiple domains. It guides developers on managing secrets, validating user input, preventing SQL injection, implementing robust authentication and authorization (including RLS), and mitigating XSS attacks. Use this when handling sensitive data, APIs, or user-generated content to ensure the highest level of security.

This skill executes the final two phases of the SPARC methodology: Refinement and Completion. It systematically reviews the implemented feature through rigorous code reviews, expands test coverage (unit, integration, edge cases), validates performance, generates a traceability matrix, creates comprehensive documentation, and confirms deployment readiness. It ensures the feature is robust, tested, and production-ready.

A comprehensive CI/CD quality gate checklist for Spring Boot projects. It guides developers through mandatory steps including building, static analysis (SpotBugs, PMD), running unit/integration tests, measuring code coverage, performing security scans (OWASP), and reviewing diffs before merging or deploying.

This comprehensive guide demonstrates how to achieve highly testable Swift code using protocol-based dependency injection. By abstracting external concerns—such as file systems, networking, and external APIs—into small, focused protocols, developers can write deterministic unit tests that mock side effects and error paths, ensuring robust architecture across different environments (App, Test, Preview).

A comprehensive, multi-stage skill designed to simulate a professional Continuous Integration (CI) pipeline. It guides users through critical quality gates, including build verification, type checking, linting, running test suites (with coverage checks), security scanning for secrets, and final diff review. Use this skill before creating a Pull Request or finalizing any significant feature to ensure code robustness and adherence to best practices.

Automates comprehensive code reviews for GitHub pull requests using parallel specialized agents. Performs eligibility checks, context gathering, multi-perspective analysis, and adversarial verification to ensure high-quality feedback. Only works on GitHub PRs, not local changes.

This comprehensive guide outlines an opinionated set of conventions for building robust Ruby on Rails applications. It covers core architectural principles, including rich models, state-as-records, minimal dependencies, and best practices for CRUD operations and testing. It is mandatory to consult these guidelines whenever designing, writing, reviewing, or refactoring any Rails code.

Scan entire codebases or specific changes, audit repositories for security issues, and generate verified patch files. Supports scanning whole repositories, branch diffs, or individual commits. Each finding is verified by an agent panel before reporting. Suggested patches are saved as files for manual review and application. Works in auto mode for streamlined security auditing workflows.

A comprehensive preflight checklist designed for authors submitting academic manuscripts to the American Economic Journal: Microeconomics (AEJ: Micro) via the AEA system. It ensures compliance with single-blind review policies, covering abstract word limits, JEL coding, data/code availability requirements, formatting, and fee confirmation before final submission.

A comprehensive guide for authors developing systems papers for major conferences (like ATC). It details how to build a reproducible story by pinning all environments (hardware, OS, toolchain, workload, code), providing turnkey one-command execution paths, and preparing a runnable, anonymized artifact package for academic review and evaluation.

A comprehensive guide detailing the strict requirements for submitting supplementary materials (video figures, code archives, data, and appendices) to major academic conferences like CHI. It emphasizes critical rules such as end-to-end anonymity, self-containment (the paper must stand alone), proper data archiving, and handling multiple submission stages (review vs. publication).

This skill automates the entire GitHub Pull Request (PR) review cycle, specifically targeting Copilot Code Review comments. It runs a robust loop: automatically triggering reviews, triaging open threads, dispatching parallel fixes that adhere to repo conventions, committing changes, and resolving comments. It continues iterating until the PR is deemed clean and ready for merge, minimizing manual effort and ensuring high code quality.