Skill UI

This is an all-in-one command-line tool for generating and editing images using the full Nano Banana model family. Users can select the optimal model—Gemini 3.1 Flash for balanced performance, Gemini 3 Pro for high-quality output, or Gemini 2.5 Flash for speed—to suit their needs. Key features include text-to-image generation, precise single image editing, and multi-image collage composition, making it versatile for creative and technical workflows.

A speed-optimized, comprehensive checklist for rapid security assessments. This guide covers full-cycle penetration testing methodologies, including deep reconnaissance (WAF bypass, CDN mapping), access control testing (MFA, JWT, API keys), and session management vulnerabilities. Ideal for time-boxed engagements, CTF competition, or initial service triage.

This guide establishes an optimized local development loop for Oracle Cloud Infrastructure (OCI). It teaches users how to bypass the slow web console by setting up dedicated CLI profiles (dev, staging, prod), managing environment variables, and creating robust shell aliases. This allows developers to perform complex operations—such as listing resources, launching instances, and managing storage—directly from the terminal, ensuring speed and consistency across all environments.

This guide provides detailed strategies for optimizing Qdrant's operational performance. It covers critical areas such as search speed (latency and throughput), efficient vector indexing strategies, and advanced memory management techniques. Use this when you need to improve the speed, scalability, and resource efficiency of your vector database deployment.

A comprehensive guide for diagnosing and resolving slow search performance in Qdrant. This resource covers issues related to low QPS (throughput), high latency for single queries, and slow filtered searches. Solutions include tuning HNSW parameters, managing memory pressure, implementing quantization, optimizing indexing, and configuring cluster settings for maximum efficiency.

Provides comprehensive strategies for minimizing API credit consumption when using SerpApi. Techniques include implementing aggressive caching with Redis, utilizing the free Archive API for historical data retrieval, and selecting the appropriate engine (like Google Light API) to balance cost and speed. Includes cost calculation models and usage monitoring scripts.

A state-of-the-art solution for real-time object detection using the advanced YOLO 2026 model. This skill detects 80+ COCO object classes (people, vehicles, animals) and outputs bounding boxes with high precision. It features automatic hardware acceleration, optimizing the model for various platforms (CUDA, MPS, OpenVINO, ROCm) to ensure maximum speed and efficiency, whether running on CPU, GPU, or Neural Engine.

This skill provides real-time object detection capabilities by leveraging the Google Coral Edge TPU accelerator. It operates natively within Windows Subsystem for Linux (WSL), allowing high-speed, low-latency inference on live camera frames. By utilizing hardware acceleration, it achieves impressive performance (e.g., ~4ms inference at 320x320), making it ideal for edge computing projects requiring rapid visual analysis and resource efficiency.

Provides direct access to real Google field data, integrating metrics from Search Console (GSC), Google Analytics 4 (GA4), and PageSpeed Insights. Analyze Core Web Vitals (CWV), CTR, impressions, organic traffic trends, indexation status, and search performance history (25-week data). Essential for technical SEO audits and marketing performance tracking.

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

A comprehensive reference guide detailing best practices, rules, and optimizations for building high-performance React Native and Expo applications. It covers critical areas such as list virtualization, complex animations, UI patterns, state management, and monorepo structure, helping developers avoid common pitfalls and maximize app speed and stability.

This skill provides a direct, fast shell invocation to capture the current git diff (staged, working-tree, or specific file list) as raw text. It is designed to replace slower LLM agent steps that merely execute 'git diff' commands, significantly speeding up CI/CD workflows and meta-steps that require repository state analysis.