Skill UI

This skill guides the definition of relationships and integration contracts between distinct bounded contexts within a complex system using Domain-Driven Design (DDD) patterns. It is crucial for preventing domain leakage, planning anti-corruption layers (ACLs), and clarifying ownership boundaries when multiple services interact, ensuring a robust and scalable system architecture.

This skill provides comprehensive methods to optimize Deepgram API usage and manage costs. It implements budget-aware transcription pipelines that preemptively check projected spending against set limits, utilizes audio preprocessing techniques (like silence removal via ffmpeg) to minimize billable minutes, and includes API calls to monitor current usage and spending against defined budgets. Ideal for cost-sensitive, production-grade deployments.

Provides reference architectures for building high-scale, reliable transcription systems using Deepgram. It covers four main patterns: synchronous REST for short files, async queues (BullMQ) for batch processing, WebSocket for real-time streaming, and a hybrid router for mixed workloads. Use this when designing production-grade audio processing pipelines.

This repository provides production-ready, structured templates for building core Decentralized Finance (DeFi) protocols using Solidity. Templates cover essential components such as staking reward systems, Automated Market Makers (AMMs), governance logic, lending/borrowing mechanisms, and flash loans. It is essential for developers aiming to build robust and scalable smart contract applications on blockchain platforms.

Automates Detrack operations through Composio’s Rube MCP toolkit by discovering available tools, managing connections, and executing workflows with schema-compliant arguments; ideal for teams integrating Detrack tasks inside Rube-driven pipelines.

A specialized guide for building robust and scalable Discord bots from scratch. Covers modern best practices, including the use of slash commands, handling gateway intents, managing rate limits, and implementing sharding. Supports foundational patterns for both Discord.js (JavaScript/TypeScript) and Pycord (Python), ensuring your bot is production-ready and highly stable.

Guidelines for building scalable, maintainable Django apps covering REST API design with DRF, ORM best practices, caching, signals, middleware, and deployment-ready project layouts and settings.

An expert AI assistant specializing in modern Django 5.x development. It provides best practices, architectural guidance, and actionable steps for building scalable, secure, and highly performant web applications. Expertise covers async views, DRF, Celery, Channels, and comprehensive CI/CD integration. Use this when building enterprise-grade Django systems.

Guides users through a three-stage workflow for collaborative documentation, helping teams gather context, iteratively refine structure, and test readability before sharing specs, proposals, or decision docs.

A comprehensive guide for deploying Documenso integrations across various cloud platforms and environments. Learn how to containerize applications using Docker, set up self-hosted instances with Docker Compose, and implement serverless functions on AWS Lambda or Google Cloud Run, ensuring secure and scalable infrastructure.

This skill provides a comprehensive framework for implementing observability for Documenso integrations. It wraps API calls using proxies to track key metrics (request counts, latency, error rates) and sets up structured logging and health checks. Use this when setting up monitoring stacks (like Prometheus/Grafana) or debugging production issues, ensuring detailed operational metrics are available.

Provides advanced patterns to significantly boost the performance and scalability of Documenso integrations. Key techniques covered include using templates to drastically reduce API round-trips, implementing metadata caching (e.g., using Redis) to minimize database lookups, and utilizing batch processing with concurrency control (p-queue) or asynchronous job queues (Bull) for handling large volumes of documents efficiently.