Skill UI

This comprehensive skill guides the systematic optimization of end-to-end application performance across the entire stack. It covers establishing performance baselines through deep profiling (CPU, Memory, I/O), assessing observability gaps, optimizing databases, tuning backend services and APIs, and enhancing frontend rendering. Ideal for complex, scalable applications that require measurable performance improvements, reliability enhancements, and adherence to modern user experience standards.

This comprehensive skill guides the systematic optimization of end-to-end application performance across the entire stack. It covers establishing performance baselines through deep profiling (CPU, Memory, I/O), assessing observability gaps, optimizing databases, tuning backend services and APIs, and enhancing frontend rendering. Ideal for complex, scalable applications that require measurable performance improvements, reliability enhancements, and adherence to modern user experience standards.

Expert in developing complete, high-performance firmware and peripheral drivers for ARM Cortex-M platforms (STM32, Teensy, nRF52). Specializes in low-level hardware interaction, including implementing drivers for I²C, SPI, UART, and managing complex concurrency patterns using FreeRTOS/Zephyr. Provides critical guidance on optimizing for determinism, cache coherency, DMA transfers, and memory barriers to ensure reliable embedded system operation.

Atheris is a coverage-guided Python fuzzer built on libFuzzer for fuzzing pure Python code and C extensions, with AddressSanitizer support to catch memory corruption and an easy harness setup for command-line fuzz runs.

Atheris is a coverage-guided Python fuzzer built on libFuzzer for fuzzing pure Python code and C extensions, with AddressSanitizer support to catch memory corruption and an easy harness setup for command-line fuzz runs.

Activation-aware weight quantization that compresses 7B-70B models to 4-bit with minimal accuracy loss, delivering ~3x inference speedups and memory reductions for constrained GPU deployments while integrating with vLLM and Marlin kernels.

A specialized skill for writing highly efficient, memory-safe, and robust C code. This guide focuses on best practices for systems programming, including rigorous memory management (malloc/free), advanced pointer arithmetic, POSIX compliance, multi-threading (pthreads), and embedded systems constraints. It emphasizes using static analysis tools, implementing comprehensive error handling, and ensuring performance through proper profiling. Ideal for complex, low-level system tasks.

Automate Cabinpanda operations through the Composio toolkit by driving Rube MCP calls, discovering the latest tool schemas, managing connections, and executing workflows with schema-compliant arguments and memory handling.

Automate Cal operations through Composio’s toolkit by routing every step via Rube MCP APIs; always begin with schema discovery, verify Cal connections, then execute inspected tools with exact arguments, session reuse, and memory placeholders.

Automate Callerapi operations by orchestrating Rube MCP’s Composio toolkit: search the latest tool schemas, verify the Callerapi connection, and run workflows through RUBE_MULTI_EXECUTE_TOOL with schema-compliant arguments and memory/session handling.

Orchestrates Cardly operations through Rube MCP and Composio, guiding users to search current tool schemas, connect the Cardly toolkit, and execute workflows via schema-compliant RUBE_MULTI_EXECUTE_TOOL calls with managed sessions and memory.

Automate Bannerbear operations through the Composio Rube MCP toolkit by discovering up-to-date tools, ensuring active connections, and executing schema-compliant operations with memory-aware multi-tool calls.