Skill UI

This comprehensive guide demonstrates the essential workflow for integrating with Customer.io using its SDK. It covers the core functions required for user lifecycle management: identifying and updating user profiles, tracking custom events (both authenticated and anonymous), and sending transactional emails. Ideal for developers performing quick customer journey mapping or initial platform setup.

A comprehensive workflow for production-grade, pre-recorded Speech-to-Text (STT) transcription using the Deepgram API. This skill supports transcribing audio from URLs or local files, offering advanced features such as speaker diarization, automatic summaries, sentiment analysis, and topic detection. It also includes robust batch processing methods for handling large datasets.

This skill provides a comprehensive and isolated setup for managing Deepgram API integrations across different deployment stages (Development, Staging, Production). It includes typed configuration management, a client factory pattern, and Docker Compose profiles, ensuring that each environment uses specific credentials, models, and feature settings (like diarization or PII redaction) without conflict. Ideal for robust, multi-stage application deployment.

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.

Automate deploying production-ready monitoring stacks like Prometheus, Grafana, and Datadog, delivering configuration files, deployment scripts, and guided instructions for infrastructure-focused observability setups.

Analyze Stitch projects and synthesize a semantic design system into DESIGN.md files

Provides practical advice on Dockerfiles, CI/CD pipelines, deployment strategies, infrastructure-as-code, and observability, helping teams containerize apps, configure GitHub Actions, plan production rollouts, and keep deployments secure and observable.

Guides users through writing, reviewing, and editing documentation with consistent structure, tone, and accuracy; ideal when creating README files, updating docs folders, or refining markdown drafts per contribution standards.

A comprehensive guide for setting up and managing Documenso across multiple deployment environments (Development, Staging, and Production). This skill details best practices for achieving environment isolation, implementing robust secret management (using .env files), creating environment-aware client factories, and setting up safety guards for secure, multi-stage deployments.

This guide provides comprehensive templates and best practices for structuring all types of technical documentation. It covers essential formats including README files, REST API endpoints, code comments (JSDoc), Changelogs, Architecture Decision Records (ADR), and AI-optimized documentation. Use these templates to ensure your project documentation is standardized, scannable, and easily consumable by both human developers and AI agents.

Provides a structured approach for creating, editing, and analyzing .docx files with tooling and best practices for tracked changes, comments, formatting, and text extraction, covering JavaScript document generation and Python OOXML editing plus markdown-based redlining.

Guides assistants through DOCX creation, editing, and redlining by describing when to unpack XML, use docx-js for new files, leverage the Document library for edits, and follow tracked-change workflows for reviews, including batching and precise OOXML edits.