Skill UI

Fuzzing Dictionary supplies domain-specific tokens to guide fuzzers when targeting parsers, protocols, configs, or file formats so they reach deeper logic; include magic bytes, headers, keywords, and combine generation from LLMs, headers, or binaries before passing via the fuzzer flag.

This skill provides comprehensive automation for content workflows using the Gamma API. It allows users to generate multiple variations from a single template, support batch processing, and specify export formats (PDF, PPTX, PNG). Furthermore, it handles the retrieval of final exported files and configures detailed sharing permissions, making it ideal for structured, large-scale content distribution.

A comprehensive mechanism for managing data privacy, retention, and compliance when integrating with Gamma APIs. This skill guides users on handling Personally Identifiable Information (PII), sanitizing user content and logs, securely archiving exported files (e.g., via S3), and implementing precise data retention policies to meet standards like GDPR and CCPA. Essential for building compliant, production-ready applications.

This guide provides a deep dive into migrating existing presentation content (from PowerPoint, Google Slides, Canva, etc.) to the modern, AI-powered format of Gamma. It details a robust, multi-step workflow: content extraction, content cleaning, and batch regeneration using scripting methods. This approach ensures that the core content is preserved while benefiting from Gamma's superior AI formatting capabilities, moving beyond simple file imports and guaranteeing better results than the original source files.

Generates production-ready Docker Compose configurations for multi-container apps by defining services, networks, volumes, health checks, and resource limits based on user architecture input.

This skill generates complete gRPC service definitions, client/server stubs, and robust implementations directly from Protocol Buffer (.proto) files. It supports all streaming patterns (unary, server, client, bidirectional) and includes advanced features like authentication interceptors, health checks, and automatic REST-to-gRPC gateway generation, making it ideal for building high-performance, enterprise-grade microservices.

Automatically analyzes source files, detects or honors the requested testing framework, and produces comprehensive unit tests with mocks, edge cases, and assertions for Jest, pytest, JUnit, and other frameworks whenever users ask to generate tests.

This guide details Apple's Human Interface Guidelines (HIG) for implementing crucial navigation components. It provides best practices for search fields (instant feedback, scoping), page controls (linear sequences), and path controls (file hierarchy/breadcrumbs). It helps developers ensure their application's UI feels native and intuitive across various Apple platforms (iOS, macOS, etc.).

This skill automatically gathers and structures comprehensive context for Apple product development. It analyzes existing project files (like README, Info.plist, and code) and prompts the user for details across product overview, target platforms, technology stack, design system, and accessibility requirements. The output is a structured context document used by other specialized skills to ensure consistent, informed design and development decisions.

A comprehensive skill designed to manage, track, and persist image assets generated by Ideogram's API. This tool addresses the critical issue of expiring image URLs by implementing a complete lifecycle pipeline. It handles metadata tracking (prompt, seed, model, style, etc.), immediate downloading, and robust storage to both local filesystems and cloud solutions like S3. Features include asset persistence, generation history logging, and image reproduction using stored seed values.

Generates and implements backup strategies for databases and applications, producing configuration files and automation scripts that ensure secure, scalable protection and disaster recovery readiness across platforms.

Guides multi-agent workflows through an iterative context retrieval loop—dispatching broad queries, evaluating relevance, refining criteria, and looping up to three times so sub-agents gather exactly the files they need without overwhelming limits.