Skill UI

Provides a workflow for authorized penetration testing across AWS, Azure, and GCP to discover IAM, storage, serverless, and compute weaknesses, leveraging Pacu, ScoutSuite, Prowler, and cloud-native tools.

Guides authorized AWS penetration testing with Pacu, covering IAM enumeration, privilege escalation scanning, data access checks, and detection validation for cloud red-team and compliance exercises.

Use GCPBucketBrute alongside gcloud IAM inspection to enumerate storage buckets, evaluate IAM bindings, and hunt privilege escalation paths during GCP security assessments.

Performs comprehensive IoT device security assessments, combining hardware interface testing, firmware extraction, runtime exploitation, and network/cloud/mobile analysis to find vulnerabilities before deployment or for product reviews.

This tool is designed for security professionals to test for Server-Side Request Forgery (SSRF) vulnerabilities. It systematically probes user-controllable URL parameters to identify access to internal network services, cloud metadata endpoints (AWS/GCP/Azure), and restricted local resources. It supports various payload techniques, including protocol handlers (gopher, file), IP encoding, and DNS rebinding, making it essential for thorough security assessments and penetration testing.

This skill provides a comprehensive guide on securely integrating and calling Firebase Cloud Functions from Flutter applications. It covers the proper use of `httpsCallable` to invoke structured server-side logic, handling data serialization, implementing robust error handling (including permission denial and timeouts), configuring regional deployments, and utilizing the Firebase Emulator Suite for reliable local testing.

Enables structured cloud penetration testing across Azure, AWS, and GCP by guiding reconnaissance, authentication, enumeration, exploitation, and persistence workflows for authorized assessments.

This utility provides a structured way to manage and separate notes across multiple accounts and environments within Apple Notes. By utilizing distinct accounts (e.g., iCloud for Production, 'On My Mac' for Development), users can ensure absolute data isolation between development, staging, and live production data. It is crucial for maintaining clean separation in complex development workflows and QA testing scenarios.

Automate the entire deployment lifecycle for ML inference services on CoreWeave GPU cloud. This workflow integrates unit testing, container image building (to GHCR), and rolling deployment to CoreWeave Kubernetes clusters via GitHub Actions. Ideal for ensuring stable, high-performance deployment of GPU-dependent models. Key features include validating GPU manifest requests and managing deployments using standard Kubernetes APIs.

This workflow provides a complete, end-to-end solution for building and deploying robust web scrapers using Crawlee on the Apify platform. It guides users through every stage: defining input schemas, setting up the Actor with a sophisticated router pattern, extracting structured data (e.g., product details), saving results to datasets, and managing the full lifecycle from local testing to cloud deployment via apify-cli.

This guide details how to set up and test Apify Actors locally using the Apify CLI. It emulates the full platform environment (including datasets, key-value stores, and request queues), allowing developers to run scrapers, test data handling, and debug the entire development lifecycle before deploying to the cloud. Perfect for rapid iteration and rigorous local testing.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.