What problem does it solve? Writing signal-processing firmware with Espressif's ESP-DSP library involves many subtle rules—FFT table initialization, normalized frequency arguments, 16-byte buffer alignment, stateful filter delay lines, and C++-only matrix/EKF classes. This Skill grounds AI code generation in the real esp-dsp repository so the generated ESP-IDF code uses correct APIs, call chains, and Kconfig settings instead of invented functions. ## Core Features & Use Cases - Scenario Recipes: 15 step-by-step recipes covering project setup, complex/real FFT, windows, DCT, FIR/IIR filters, resamplers, vector math, matrices, 2D convolution, Kalman EKF, and real-time streaming audio (sc16 spectrum and IIR effects chains). - Real API Reference: Function signatures, structs, error codes, and Kconfig options extracted from the actual esp-dsp headers, plus a pitfalls list of 17 common mistakes with wrong/right code pairs. - Use Case: Ask for a 1024-point FFT spectrum on ESP32-S3 and receive a complete app_main with dsps_fft2r_init_fc32, windowing, bit-reverse, power-spectrum conversion, and the correct idf.py build commands. ## Quick Start Ask the AI to generate an ESP-IDF project that computes a windowed FFT spectrum of a test tone on ESP32-S3 using the esp-dsp component.