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iot

Skill

Deep-dive into AWS IoT architecture, device connectivity, edge computing, and fleet management. This skill should be used when the user asks to "design an IoT solution", "connect devices to AWS", "set up MQTT messaging", "configure IoT rules", "provision a device fleet", "use Greengrass at the edge"

0IoT

Install

git clone https://github.com/aws-samples/sample-claude-code-plugins-for-startups.git ~/.claude/skills/iot

What is iot?

Deep-dive into AWS IoT architecture, device connectivity, edge computing, and fleet management. This skill should be used when the user asks to "design an IoT solution", "connect devices to AWS", "set up MQTT messaging", "configure IoT rules", "provision a device fleet", "use Greengrass at the edge", "build a device shadow", "set up IoT security", "manage OTA updates", "store telemetry data", "create IoT topic rules", "configure fleet provisioning", or mentions IoT Core, MQTT, Greengrass, Device Shadow, IoT Rules Engine, IoT Events, IoT SiteWise, fleet indexing, or device certificates.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~148 tokens of context used while enabled, before you invoke anything

Documentation

README · ~17 min read

Specialist guidance for AWS IoT. Covers IoT Core (MQTT, shadows, rules engine), Greengrass v2 edge compute, fleet provisioning, security, data storage patterns, and fleet management.

Process

  1. Identify the IoT workload characteristics: device count, message frequency, payload size, connectivity (always-on vs intermittent), edge processing needs
  2. Use the awsknowledge MCP tools (mcp__plugin_aws-dev-toolkit_awsknowledge__aws___search_documentation, mcp__plugin_aws-dev-toolkit_awsknowledge__aws___read_documentation, mcp__plugin_aws-dev-toolkit_awsknowledge__aws___recommend) to verify current IoT Core limits, Greengrass component versions, and service quotas
  3. Select the appropriate IoT services using the decision matrix below
  4. Design the communication and data ingestion topology (protocols, topics, rules)
  5. Configure security (X.509 certificates, IoT policies, fleet provisioning method)
  6. Design data storage and analytics pipeline
  7. Plan fleet management (jobs, indexing, Device Defender)
  8. Recommend operational best practices (monitoring, OTA updates, edge deployments)

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