Skill UI

This skill automatically generates comprehensive unit tests based on provided source code. It supports multiple programming languages (Python, JavaScript, Java, Go, Rust) and popular testing frameworks (pytest, Jest, JUnit). Use it to improve code coverage, test boundary conditions, and validate error handling efficiently, saving manual testing time.

This skill provides an end-to-end solution to transform existing REST APIs, defined by OpenAPI or Swagger specifications, into functional MCP servers. It maps every API operation to a dedicated, callable LLM tool, automatically generating robust parameter schemas (Zod) and handling authentication wiring. Use this to expose internal or third-party APIs to LLMs, providing a complete workflow from spec ingestion to local testing and cloud deployment.

Comprehensive tool for developing, testing, and deploying Miaoda/Spark applications. It supports three distinct development paths: local full-stack development, static HTML hosting, and cloud AI session generation. Use it for creating new internal tools, managing databases, and publishing final, shareable versions to the cloud.

This technical skill is designed to verify the compatibility of the Codex CLI with skills compiled from MDA source. Loading this skill confirms that the CLI loader successfully parses the SKILL.md format, adhering to the agentskills.io v1 envelope subset. It is primarily used for testing build pipelines, metadata integrity, and ensuring robust compatibility between MDA compilation and runtime ingestion.

This skill provides an end-to-end, highly reproducible workflow for bulk RNA-seq differential expression analysis. It orchestrates the entire pipeline, guiding users from raw FASTQ reads through Quality Control (QC), trimming, alignment (STAR/Salmon), quantification, generating a gene-level counts matrix, and finally executing differential expression testing (pydeseq2) and pathway enrichment analysis. It is designed for robust, statistically sound, and fully documented results.

This orchestrator acts as a central hub for Go development, managing the complexity of modern software projects. Instead of using single skills, it reads the task context (e.g., building gRPC, debugging a panic) and automatically loads the most relevant combination of specialized skills (like testing, error handling, safety, or security) simultaneously. It ensures comprehensive coverage throughout the entire Go development lifecycle, making it ideal for advanced AI coding agents.

A comprehensive, end-to-end quality assurance and validation checklist for fullstack Next.js applications. This guide details steps—including TypeScript checks, linting, unit testing, SEO meta tag verification, route regression, and post-deployment smoke tests—required to ensure an application is production-ready before every major release.

This skill helps manage and execute steps within a Test-Driven Development (TDD) workflow cycle. Note that this skill serves as an alias for `tdd-workflows-tdd-cycle`, maintaining discoverability. It guides users through the complete TDD development cycle, ensuring structured testing and validation steps.

This deployment skill is designed to be integrated into the Playwright testing workflow. Its primary function is to validate the loading process of shared skills across the entire environment during the startup phase. It ensures that all necessary components and modules are correctly registered and available for reliable End-to-End (E2E) testing execution.

This meta-skill runs three essential quality gates (ruff, mypy, and pytest) concurrently against the staged changes. It provides a comprehensive, CI-like check locally, offering a single BLOCK or APPROVE verdict to ensure code readiness before committing. It combines static analysis, type checking, and unit testing into one workflow.

A specialized internal helper for deep meta-stack trace investigation in Python environments. This tool guides users through generating Python-specific root-cause checks, creating minimal reproducible test cases using pytest, and identifying precise targets for defensive patches (e.g., validation or guard clauses). It ensures robust debugging and testing practices.

Unship is a dedicated local workflow for front-end developers to compare multiple AI-generated UI alternatives (such as layouts, copy, or flows) directly within a running application environment. Instead of committing to one generated version, it adds temporary source-level variants, allowing for visual comparison. After the user selects the final version, the skill automatically cleans up all unused temporary code and attributes, ensuring a clean, production-ready codebase. Note: This tool is for local iteration only, not for production A/B testing or analytics.