Skill UI

This skill provides a comprehensive framework for creating, writing, and optimizing newsletters tailored for developer audiences. It covers content strategy (e.g., 70-20-10 rule), defining newsletter types (curated links, product updates), crafting engaging subject lines, and structuring technical emails for maximum readability and engagement.

EAS Observe is a comprehensive tool for monitoring performance metrics in production Expo applications. It tracks critical performance data, including app startup time, navigation performance across routes, and custom user events. Developers can integrate it into their Expo project using the `expo-observe` package and query detailed reports via the EAS CLI, ensuring optimal user experience and stability.

A portable, framework-agnostic system designed for robust field-side observability in React or React Native apps. It establishes a strongly typed event taxonomy, ensures best-effort, non-blocking data fan-out across multiple analytics providers, and enforces consent gates for all telemetry data. This system complements synthetic testing by capturing real user vitals (LCP, INP, CLS) and behavioral events in production.

This skill guides developers on building real-time, bidirectional, and multimodal streaming applications using the Gemini Live API. It covers low-latency voice, video, and text streaming over WebSockets, incorporating advanced features like Voice Activity Detection (VAD), function calling, and secure session management. Ideal for conversational AI, interactive video conferencing, and complex real-time user experiences.

Use this powerful skill to perform advanced, multi-modal video generation and editing using the official google-genai SDK. Capabilities include generating realistic videos from text prompts (Text-to-Video), animating scenes from a single input image (First-Frame-to-Video), and applying style or character references from images. It also supports complex video refinement, inpainting, and optimizing source footage for professional creative workflows.

This skill guides users on optimizing their GitHub presence for maximum discoverability and professional appeal. It covers best practices for writing compelling README files, structuring comprehensive profile READMEs, and strategically implementing trust badges and marketing elements to enhance project visibility and adoption.

A comprehensive guide for developers building AI demos and GPU compute tasks on Hugging Face Spaces using ZeroGPU hardware. It covers best practices for writing and reviewing code that utilizes the `@spaces.GPU` decorator, managing runtime duration and quota, and understanding the specific CUDA availability model and process isolation rules required for reliable ML deployment.

This specialized guide assists service-area businesses (e.g., plumbing, HVAC, appliance repair) in mastering local SEO. It provides comprehensive strategies for auditing Google Business Profiles (GBP), generating high-ranking neighborhood service pages, ensuring NAP consistency, and implementing local schema markup to dominate the Google Map Pack.

This skill generates a detailed, step-by-step, interprocedural execution trace for a given piece of code and specific input scenario. It resolves name ambiguities, tracks type transitions, and highlights non-obvious behaviors (like implicit coercions or side effects). Use it when a user is confused about how code behaves, allowing for a deep dive into the actual execution path to clarify assumptions versus reality.

A systematic skill designed to investigate data incidents, including freshness delays, volume anomalies, schema changes, and ETL failures. It guides the agent through a comprehensive process using Monte Carlo's observability metadata and optional direct data querying to pinpoint the root cause.

This skill integrates with Monte Carlo's observability platform to provide a comprehensive health report for data assets. It checks critical metrics including data freshness, active alerts, monitoring coverage, asset importance, and the health of upstream dependencies. Activates when users inquire about the status, reliability, or quality of a data table.

This skill provides comprehensive monitoring advisory services for data assets and AI agents. It helps users assess data coverage gaps, analyze use-case criticality, and automatically create data quality monitors (table, metric, validation). Furthermore, it enables monitoring of AI agent performance, latency, and observability, ensuring robust data governance across the entire ML lifecycle.