Skill UI

A comprehensive guide for connecting resource-constrained microcontrollers (like Arduino) to Azure IoT Hub and IoT Edge. It provides structured patterns for secure provisioning, handling intermittent networks (store-and-forward), robust telemetry transmission (MQTT over TLS), and implementing local edge decision-making for industrial and field deployments.

This tool assists engineers in transforming vague work logs into structured, evidence-backed impact statements for professional documentation. It uniquely mines Copilot CLI session logs, git commits, and GitHub PRs to reconstruct forgotten work. It enforces a mandatory 'Action → Result → Evidence' impact contract, making it indispensable for preparing performance reviews, promotion packets, and self-assessments.

A comprehensive guide to using `go.uber.org/dig` for implementing dependency injection in Go. It covers core concepts like `Provide`/`Invoke`, parameter object embedding (`dig.In`), result objects (`dig.Out`), named values, value groups, and making providers as interfaces. Ideal for setting up application graphs at startup in Go projects.

Uber FX is a robust application framework designed for building long-running Go services. It combines a reflection-based dependency injection (DI) container (built on dig) with essential features like lifecycle hooks (OnStart, OnStop), modular composition, and signal-aware execution. It ensures proper service initialization, graceful shutdown, and structured wiring for production-grade Go applications.

This skill guides the process of transforming private, repetitive operational workflows developed in Hermes into sanitized, reusable artifacts suitable for the public ECC layer. It ensures that sensitive data, local file paths, personal credentials, and private state are stripped out, allowing the core pattern to be safely published for broader use.

This skill guides the end-to-end development, implementation, and validation of production-ready Python modules for Azure IoT Edge. It covers critical aspects including telemetry processing, protocol adaptation (Modbus, OPC-UA), local inference, and ensuring robust, secure edge-to-cloud messaging under variable network conditions.