What problem does it solve? Developing vision AI firmware with Espressif's ESP-WHO framework involves a strict pipeline model, BSP-to-target validation, model injection ordering, and FreeRTOS task lifecycle rules that are easy to get wrong, causing build failures or runtime assertion crashes. This Skill grounds AI agents in the real esp-who repository APIs, configurations, and pitfalls so generated code compiles and runs correctly. ## Core Features & Use Cases - Scenario Recipes: Eight step-by-step recipes covering project setup, object detection with LCD or serial output, custom detection apps, face recognition enrollment/recognition/deletion, QR code recognition, frame capture pipelines, camera selection, and task lifecycle control. - API and Configuration Reference: Real class and method signatures for WhoTask, WhoFrameCap, WhoCam variants, WhoDetect, WhoRecognition, WhoQRCode, and app wrappers, plus Kconfig symbols, sdkconfig defaults, partition tables, and DETECT_MODEL mappings. - Pitfall Prevention: Sixteen documented pitfalls with WRONG/CORRECT code pairs, such as missing IDF_EXTRA_ACTIONS_PATH, BSP/target mismatch, omitted set_model calls, and insufficient fb_count. - Use Case: A developer asks the agent to build a face recognition app on an ESP32-S3-EYE; the Skill walks through mounting the FATFS database, constructing the DVP frame capture pipeline, instantiating WhoRecognitionAppLCD, and building with the correct sdkconfig.bsp file. ## Quick Start Ask the agent to create an ESP-WHO object detection example for the ESP32-S3-EYE board using the human_face_detect model and generate the build commands.