Skill UI

A specialized workflow guide for comprehensive security testing of REST and GraphQL APIs. It systematically covers critical security aspects such as authentication validation (OAuth2, JWT), authorization checks (IDOR, privilege escalation), input validation (SQL/NoSQL injection), rate limiting enforcement, and secure error handling. Ideal for vulnerability assessment, bug bounty programs, and pre-deployment security audits.

An expert developer specializing in secure backend coding practices, vulnerability mitigation, and robust API design. Proficient in preventing common attacks such as SQL injection, XSS, and CSRF. Covers comprehensive areas including input validation, authentication mechanisms (OAuth 2.0, MFA), database security, and implementing necessary security headers (CSP, HSTS) for building secure-by-design applications. Ideal for implementing security fixes or building new, hardened backend services.

Guides GCP users through automating Cloud Scheduler job creation with best practices, ready-to-run code, and validation, ideal for implementing cron-driven workloads across compute, storage, BigQuery, Vertex AI, and Cloud Run.

An expert AI specialist that integrates advanced static analysis (e.g., CodeQL, SonarQube) with modern DevOps practices. It performs multi-layered code reviews, checking for security vulnerabilities, performance bottlenecks, architectural flaws, and adherence to best practices across various languages. Ideal for CI/CD pipelines and pull request validation.

This skill executes CodeRabbit's core workflow, providing automated, in-depth code reviews directly on pull requests. It analyzes code diffs based on custom rules (e.g., API validation, DB security), generates detailed walkthrough summaries, and posts line-level feedback. Ideal for setting up robust CI/CD quality gates and maintaining high code standards throughout the development lifecycle.

This skill converts vague coding requests into a highly structured, actionable, and atomic development plan. It guides the user through defining the approach, scope (In/Out), and breaking down the task into a mandatory checklist of ordered, concrete steps (e.g., discovery, implementation, validation). Ideal for ensuring comprehensive and traceable project development workflows.

This guide provides production-ready patterns for integrating the Firecrawl SDK in TypeScript and Python. It covers essential architectural best practices, such as implementing singleton clients, typed service wrappers, automatic retries with exponential backoff, concurrency management, and robust response validation using Zod. Ideal for building scalable, reliable web scraping services.

Generate complete, production-ready REST API implementations from existing OpenAPI specifications or database schemas. This skill scaffolds all necessary CRUD endpoints (GET, POST, PUT, DELETE) across multiple frameworks (Express, FastAPI, Spring Boot, etc.), automatically incorporating features like pagination, filtering, validation, and robust authentication middleware. Ideal for rapidly bootstrapping complex backend services from defined data models.

Automates guidance for managing Kubernetes secrets, covering best practices, Terraform/Helm patterns, and IaC validation ideal for advanced DevOps scenarios.

A comprehensive tool for detecting critical API security vulnerabilities, including injection, broken authentication (BOLA), excessive data exposure, and mass assignment. It audits endpoints against the OWASP API Security Top 10 standards by analyzing source code, middleware chains, and request validation logic. Ideal for pre-deployment security gates, CI/CD integration, and compliance audits.

This skill provides a practical guide for comprehensive accessibility validation of web applications. It helps users test compatibility with various screen readers, validate ARIA implementations, and debug issues related to assistive technologies. Ideal for ensuring that web forms, dynamic content, and navigation are fully usable by people with disabilities.

A comprehensive meta-skill for validating, testing, and scoring the quality of technical skills within an ecosystem. It performs deep structural checks (SKILL.md compliance), executes Python scripts for syntax, runtime, and output validation, and generates multi-dimensional quality scores using letter grades and tier recommendations. Ideal for new skill authorship, auditing existing components, or integrating rigorous QA gates into CI/CD pipelines.