291 skills · sorted by relevance
Create AI video clips from text or reference images, choosing among providers to match the task and budget. Supports vertical social videos, product photo animation, and conversational editing of existing clips with Gemini Omni Flash.
Turn descriptions of scientific components and relationships into PNG diagram drafts with Nano Banana 2. Gemini 3.7 Flash reviews each draft and may request one revision, while saved image versions and review logs support manual checking.
Build decentralized finance contracts from Solidity templates for staking and token swaps. Examples cover reward distribution, adding and removing pooled tokens, and swap calculations, with additional patterns for governance and flash loans.
Build and improve mobile apps with React Native and Expo using prioritized implementation rules. Covers faster lists, animations, images, navigation, state management, and native dependencies, with explanations and code examples for reviewing common implementation choices.
Create coordinated combat visual effects in Three.js, combining branching lightning, a storm orb, black trails, sparks, and impact frames. A shared clock keeps charge-ups, dashes, and hits synchronized, including brief pauses that emphasize contact.
Measure and optimize claude-flow v3 startup, search, attention processing, and memory use. Compare benchmarks against performance targets, track changes over time, and identify regressions to guide further optimization.
Use this skill for generative video editing, text-to-video, image-referenced video generation, first-frame-to-video, first-and-last-frame transitions, and video extensions using Gemini Omni 1.1 Flash (gemini-omni-1.1-flash) via the official google-genai SDK. Includes workflows for pre-processing/optimizing high-resolution or long source videos with ffmpeg, stripping audio for full sound regeneration, and handling turn-by-turn video editing and parallel execution.
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Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
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Flash the FPGA on an HSB board connected to an NVIDIA devkit. Supports HSB Lattice boards (FPGA versions 2407, 2412, 2507, 2510) and Leopard Imaging VB1940 "all-in-one" cameras (FPGA versions 2507, 2510). Uses release-specific YAML manifests and board-type-specific program commands. Lattice and VB1940 commands must never be mixed.
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Provides Gemini CLI delegation workflows for large-context analysis and complex reasoning using Gemini 3.0 Flash and Gemini 3.0 Pro models, including English prompt formulation, execution flags, and safe result handling. Use when the user explicitly asks to use Gemini for tasks such as broad codebase analysis, fast iterations with Gemini 3 Flash, or deep architectural reasoning with Gemini 3 Pro. Triggers on "use gemini", "delegate to gemini", "run gemini cli", "ask gemini", "use gemini for this task", "use gemini 3 flash", "use gemini 3 pro".
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ApiFlash integration. Manage Organizations, Pipelines, Projects, Users, Filters. Use when the user wants to interact with ApiFlash data.
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Plan, generate, edit, and quality-check still images with Google's Gemini native image models (Nano Banana), including Gemini 3.1 Flash Image, Gemini 3.1 Flash-Lite Image, Gemini 3 Pro Image, and legacy Gemini 2.5 Flash Image. Use for model and API-route selection, conversational editing, multi-reference composition, thinking and Google Search grounding, resolution/aspect-ratio control, exact-text and brand workflows, SynthID/provenance, safety, privacy, rights, and migration from legacy Gemini or Imagen image endpoints. Do not use for Veo/video generation or Gemini Live/audio work.
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Storage management for Zephyr RTOS. Covers Non-Volatile Storage (NVS) for persistent settings, flash partition management in Devicetree, and runtime flash layout access. Trigger when implementing persistent data storage, managing flash wear leveling, or configuring device partitions.
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Firmware development for the 40-pin "Black Pill"-format board with an STM32F401RCT6 (STM32F401RC, LQFP64, 256 KB flash, 64 KB RAM, 84 MHz) that ships with the WeAct Studio HID Bootloader (USB 0483:572A, flash 0x08000000-0x08003FFF, app at 0x08004000) — its PC13 LED, KEY button on PA0, 25 MHz HSE, USB-C on USB_OTG_FS, and the PlatformIO + STM32Cube HAL setup around them, including a USB CDC virtual COM port for printf debugging. Use when working on this board, an unbranded F401RCT6 Black Pill clone, or any STM32F401/F411 board that enumerates as "WeAct Studio HID Bootloader": project setup, platformio.ini, linking at 0x08004000, flashing through the HID bootloader or ROM DFU, the app starting behind a bootloader (VTOR, SysTick, clock hand-off), clock/PLL configuration for 84 MHz plus 48 MHz USB, printf/serial console over USB (no /dev/cu or COM port), a blink that never starts or hangs in HAL_Delay, entering or recovering the bootloader, or debugging why something on the board does not work.
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Firmware development for the 38-pin ESP32-WROOM-32 development board — Espressif ESP32-DevKitC V4, Ai-Thinker NodeMCU-32S, DOIT ESP32 DevKit V1 38-pin and their CH340/CP2102 clones, 19 pins per side, with GPIO0 and the six in-package flash pins (GPIO6-11, labelled D0 D1 D2 D3 CMD CLK or SD0-SD3) broken out. Use when working on a 38-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 or ESP32-WROVER module): project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, the flash-pin and IO0 traps, WROVER GPIO16/17 PSRAM conflict, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, deep sleep and RTC wake pins, flashing, BOOT/EN recovery, brownouts, or debugging why something on the board does not work.
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Firmware development for the WeAct Studio "Black Pill" (STM32F411CEU6) and its clones such as the DFRobot DFR0864 — the 25 MHz HSE and 32.768 kHz LSE crystals, PC13 LED, K1 button, USB-C wired straight to USB_OTG_FS, ROM DFU flashing, the SPI-flash footprint, and the STM32Cube HAL + PlatformIO setup around them. Use when working on this board or any STM32F411CE/F401CC Black Pill: project setup, platformio.ini, clock and PLL configuration for 96 MHz plus 48 MHz USB, pin mapping on the 48-pin package, USB CDC console, RTC on the LSE crystal, the internal temperature sensor, ADC accuracy, DFU flashing and recovery, or debugging why something on the board does not work.
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Firmware development for the WeAct Studio RP2350A Core Board (RP2350A — dual Cortex-M33 @ 150 MHz, 520 KB SRAM, 4 MB or 16 MB QSPI flash) in both of its revisions, RP2350A_V10 and RP2350A_V20 — the 40-pin Pico-2-shaped header, 3-or-4-channel 12-bit ADC, PWM, PIO, USB-C CDC, the V1.0 LDO vs V2.0 buck-boost power wiring, and the PlatformIO + arduino-pico (earlephilhower) setup around them. Use when working on this board, a WeAct RP2350 core board of unknown revision, or any Raspberry Pi Pico 2 / RP2350A clone: project setup, platformio.ini, board = rpipico2 vs weact_rp2350b, telling V1.0 and V2.0 apart, pin mapping, LED and KEY pins, powering it from a battery, 4 MB vs 16 MB flash, erratum RP2350-E9 pull-down trouble, BOOT/RESET UF2 flashing, or debugging why something on the board does not work.
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Разработка прошивок для BE-U1000 (Baikal Electronics / Байкал Электроникс, три ядра RISC-V: BR-350 и BM-310) на отладочных платах EVU-BA-2.1, EVU-BA-2.0 и EVU-BA-1.2 — её eFlash и QSPI flash, UART0/BootROM CLI, PWMA (захват и импульсы), АЦП с DMA, CAN FD, SPI, WDT, CLIC, а также SDK Байкала и его система сборки на make. Use when working on this board or any BE-U1000 / BMCU_U project (SDK 2.1/2.3, riscv32-none-elf, dfu-util, OpenOCD): настройка проекта, Makefile и MEM_REG_ROM, карта выводов и разъёмы XP1/XP8/XP9/XP10, режимы начальной загрузки и страповые выводы, прошивка по UART XMODEM либо USB DFU, работа с eFlash и TCM, прерывания и CLIC, отладка по JTAG — и разбор, почему плата молчит, не стартует, зависает или почему периферия «настроилась», а обмена нет.
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Firmware development for the 30-pin NodeMCU ESP8266 devkit — NodeMCU DevKit V1.0 / Amica (CP2102) and LoLin NodeMCU V3 (CH340G), built on the Ai-Thinker ESP-12E or ESP-12F module (ESP8266EX, 4 MB flash), with PlatformIO and the Arduino ESP8266 core (`board = nodemcuv2`). Use when working on a NodeMCU, ESP-12E, ESP-12F or ESP8266 devkit: project setup, platformio.ini, the D0-D10 vs GPIO numbering, which pins are safe and which break the boot, GPIO15/GPIO0/GPIO2 strapping, the A0 divider and 1 V ADC, software I2C and software PWM, analogWrite range, LittleFS and flash layouts, OTA, deep sleep and the missing GPIO16-to-RST link, Wi-Fi, heap exhaustion, watchdog and Soft WDT resets, exception decoding, flashing over CP2102/CH340, or debugging why the board does not boot, prints garbage, or reboots by itself.
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Firmware development for the 36-pin ESP32-WROOM-32 development board — the original DOIT ESP32 DevKit V1 with 18 pins per side, i.e. the 30-pin layout plus the six in-package flash pins (SD0 SD1 SD2 SD3 CMD CLK = GPIO6-11) broken out at the USB end, CH340G or CP2102 bridge, AMS1117 LDO, user LED on GPIO2, GPIO0 not on the header. Use when working on a 36-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 module), or when identifying which ESP32 board size you have: project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, the flash-pin trap, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, deep sleep and RTC wake pins, flashing, BOOT/EN recovery, brownouts, or debugging why something on the board does not work.
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Use when creating, testing, or updating active-recall flashcards grounded in session concepts to reinforce retention.
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Use Intel CHIPSEC to assess platform firmware configuration, SPI flash write protection, BIOS lock, SMM/SMRR, and Secure Boot variable state, dump SPI flash, and triage UEFI variables for firmware-level threats.
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Spaced-repetition flashcard system. Create cards from facts or text, chat with flashcards using free-text answers graded by the agent, generate quizzes from YouTube transcripts, review due cards with adaptive scheduling, and export/import decks as CSV.
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Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.
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