Best for
- "I want to connect Arduino sensors to Azure"
- "How do I send MQTT telemetry to IoT Hub?"
- "I need an edge gateway for field devices"
github/awesome-copilot/skills/arduino-azure-iot-edge-integration/SKILL.md
Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.
Decision brief
Use this skill when the user needs to connect Arduino-class devices to Azure IoT, especially in edge-heavy scenarios (gateways, intermittent networks, offline buffering, and local actuation).
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/github/awesome-copilot --skill "skills/arduino-azure-iot-edge-integration"Inspect the Agent Skill "arduino-azure-iot-edge-integration" from https://github.com/github/awesome-copilot/blob/9933dcad5be5caeb288cebcd370eeeb2fc2f1685/skills/arduino-azure-iot-edge-integration/SKILL.md at commit 9933dcad5be5caeb288cebcd370eeeb2fc2f1685. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Before recommending an IoT Edge topology or runtime behavior, review:
Use this skill for requests such as:
Before proposing firmware, wiring, or communication implementation details, consult official Arduino sources first:
Produce a secure end-to-end reference path from the Arduino device to cloud insights.
Use when connectivity is stable and cloud latency is acceptable.
Permission review
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 85/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 37,126 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Use this skill when the user needs to connect Arduino-class devices to Azure IoT, especially in edge-heavy scenarios (gateways, intermittent networks, offline buffering, and local actuation).
Use this skill for requests such as:
Before recommending an IoT Edge topology or runtime behavior, review:
If documentation cannot be consulted, proceed with explicit assumptions and highlight them in a dedicated section.
Before proposing firmware, wiring, or communication implementation details, consult official Arduino sources first:
When choosing between implementation alternatives, prioritize official Arduino guidance over community snippets unless there is a clear technical reason to deviate.
Use when connectivity is stable and cloud latency is acceptable.
Use when links are constrained, local control is required, or batching improves cost/reliability.
Define:
Require:
Plan and document:
Define routes for:
Specify minimum operations telemetry:
When relevant, combine with:
azure-smart-city-iot-solution-builder for city-wide architecture and phased rollout.azure-resource-visualizer for relationship diagrams.appinsights-instrumentation for app and service telemetry patterns.Also use references/arduino-official-best-practices.md as a quality baseline for firmware and hardware recommendations.
Always provide:
Alternatives
K-Dense-AI/scientific-agent-skills
Use when working directly with the `esm` Python SDK, ESM3 or ESMC model IDs, Forge/Biohub inference clients, or ESMFold2 folding workflows.
wshobson/agents
Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.
wshobson/agents
Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens —
github/awesome-copilot
Two related workflows for a locally-cloned codebase, in one skill. Documentation mode produces a single, comprehensive, verifiable architecture document primarily by reading files on disk (local-first) — use it whenever the user wants to understand, map, document, research, or onboard onto a codebase ("research this repo", "write up the architecture", "do an architecture deep dive", "document how this codebase works", "map the system design", "create an onboarding doc"). Modernization mode gener