Skills for Codex
wedsamuel1230/arduino-skills
arduino-code-generator
Generate Arduino/embedded C++ code snippets and patterns on demand for UNO/ESP32/RP2040. Use when users request Arduino code for sensors, actuators, communication protocols, state machines, non-blocking timers, data logging, or hardware abstraction. Generates production-ready code with proper memory management, timing patterns, and board-specific optimization. Supports DHT22, BME280, buttons, I2C/SPI, EEPROM, SD cards, WiFi, and common peripherals.
klutchell/claude-skills
balenify
Guide for converting Docker projects to run on balenaCloud. Use this skill when balenifying or converting an existing Docker/docker-compose project for balena, writing or modifying Dockerfile.template files, setting up docker-compose.yml for balena fleets, choosing between Dockerfile.template and plain Dockerfile for balena services, debugging balena build failures, converting volume mounts for balena, handling environment variables on balena, configuring hardware access (GPIO, USB, serial) for containers, or understanding balena networking. Also use when the user mentions balena device types, %%BALENA_ARCH%%, %%BALENA_MACHINE_NAME%%, balenalib base images, bh.cr registry references, or asks how to run something on balena.
edgeimpulse/agent-tools
build-custom-deployment-blocks
Author Edge Impulse custom deployment blocks (Enterprise). Use when asked to scaffold, modify, test, or push a custom deployment block — including Dockerfile, parameters.json schema, the build script that reads deployment-metadata.json and produces deploy.zip, and the edge-impulse-blocks CLI workflow.
edgeimpulse/agent-tools
api
Work with the Edge Impulse Studio, Ingestion, and Remote Management APIs; CLI tools; Linux runners; SDKs; and custom blocks. Use for project and sample management, data upload, model training and testing, deployment builds, device control, job monitoring, automation, or any programmatic Edge Impulse platform integration.
mpous/ai-skills
arduino-unoq-applab
Comprehensive guide for adapting applications for the Arduino UNO Q, integrating them into the Arduino App Lab ecosystem as apps and bricks, deploying Edge Impulse ML models, and building Flask-based web UIs. Use this skill when users ask about Arduino UNO Q development, App Lab apps/bricks, ML model deployment, or converting existing projects into App Lab-compatible applications.