Skill UI

A comprehensive guide and implementation for setting up a fast, cost-effective local development loop for the Perplexity Sonar API. It includes generating type-safe client wrappers, utilizing fixtures for reliable mocking, and establishing a complete test suite with hot-reloading capabilities. This ensures stable development and manages high API call costs during iteration.

This comprehensive guide details the complete workflow for setting up and maintaining a local Supabase development environment. It utilizes Docker and the Supabase CLI to run the entire full-stack service (Postgres, Auth, Storage, etc.) locally. It guides developers through initialization, creating version-controlled migrations using diff, seeding data, and performing clean database resets, ensuring local iteration accurately mirrors production capabilities.

This guide establishes a fast, reproducible local development workflow for GPU workloads using Vast.ai. It covers key practices such as testing Docker images locally (in CPU mode), mocking external APIs like Vast.ai, and implementing robust unit and integration tests. This is essential for minimizing cloud GPU costs and accelerating the iteration cycle for complex AI/ML projects.

This guide details how to set up a full local development loop for applications deployed to Vercel. It covers using `vercel dev` to emulate serverless functions, managing environment variables, and implementing hot reloading. It provides step-by-step instructions for local testing of API routes and frontends, ensuring a fast and accurate iteration cycle before production deployment.

This skill simulates an expert software engineer and systems analyst. It is designed for deep, evidence-based understanding of complex codebases. Users can ask "how does X work" or request architectural reviews, ensuring every claim is grounded in actual code paths, data flows, and dependency chains, following a rigorous multi-iteration process.

Design research posters with HTML/CSS templates that export to PDF or PPTX when PowerPoint format is explicitly requested, integrating responsive layouts and AI-generated visuals for quick preview and iteration.

Guides execution of implementation plans by dispatching isolated subagents per task, enforcing a spec-first then quality review loop, and preserving overall coordination context for faster, high-quality iterations.

This skill guides the creation, refinement, and iteration of highly personalized B2B cold outreach email sequences. It ensures that all communications sound genuinely human and thoughtful, avoiding the tone of a 'sales machine.' Users can utilize it to write initial first-touch emails, build multi-stage follow-up campaigns, or analyze performance data (open/reply rates) to improve underperforming sequences. Ideal for sales development representatives (SDRs) and marketing professionals focusing on unsolicited prospect engagement.

Allows users to resume an interrupted or paused autoresearch experiment. It automatically loads the full context, including configuration, strategy files, complete results history, and recent code changes. The system then summarizes the current best metrics and patterns, prompting the user to continue with a single iteration, set up an automated loop, or manually review the results.

Trackio is an essential library for logging, visualizing, and analyzing machine learning training experiments. It provides multi-interface support: a Python API for real-time metric logging and alert firing during training; a Command Line Interface (CLI) for retrieving historical metrics and alerts; and synchronization capabilities to Hugging Face Spaces for persistent dashboards. This tool is crucial for debugging, diagnosing training issues (like loss spikes), and automating ML workflow iteration.

A comprehensive multi-agent feedback loop inspired by Generative Adversarial Networks (GANs), designed to build complex, production-ready applications. It separates generation from evaluation, using a 'ruthlessly strict' evaluator (QA) to drive continuous iteration. This process ensures high design quality, robust functionality, and originality, overcoming the limitations of single-agent self-critique. Ideal for full-stack feature development and complex product specification implementation.

A comprehensive guide on utilizing Firebase Remote Config within Flutter applications. Learn how to implement dynamic feature flags, execute A/B testing, manage remote parameter defaults, and fetch real-time configuration values. This skill allows developers to modify app behavior and user experiences without requiring an app store update, ensuring fast iteration and efficient product testing.