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Found 470 Skills
Analyze application logs from the .evlog/logs/ directory. Use when debugging errors, investigating slow requests, understanding request patterns, or answering questions about application behavior. Reads structured NDJSON wide events written by evlog's file system drain.
Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
Implement and configure Syncfusion Angular Scheduler (Schedule) component for calendar and event management. Use this when building schedulers, calendar systems, event management applications, appointment booking interfaces, or resource scheduling solutions. This skill covers timeline views, day/week/month views, recurring events, time slot management, and working hours configuration.
Expert guidance for writing C (C99/C11) and C++ (C++17) code for embedded systems and microcontrollers. Use this skill whenever the user is working with: STM32, ESP32, Arduino, PIC, AVR, nRF52, or any other MCU; FreeRTOS, Zephyr, ThreadX, or any RTOS; bare-metal firmware; hardware registers, DMA, interrupts, or memory-mapped I/O; memory pools, allocators, or fixed-size buffers; MISRA C or MISRA C++ compliance; smart pointers or RAII in embedded contexts; stack vs heap decisions; placement new; volatile correctness; alignment and struct packing; C99/C11 patterns; C and C++ interoperability; debugging firmware crashes, HardFaults, stack overflows, or heap corruption; firmware architecture decisions (superloop vs RTOS vs event-driven); low-power modes (WFI/WFE/sleep); CubeMX project setup; HAL vs LL driver selection; CI/CD for firmware; embedded code review; MPU configuration; watchdog strategies; safety-critical design (IEC 61508, SIL); peripheral protocol selection (UART/I2C/SPI/CAN); linker script memory placement; or C/C++ callback patterns. Also trigger on implicit cues like "my MCU keeps crashing", "writing firmware", "ISR safe", "embedded allocator", "no dynamic memory", "power consumption", "CubeMX regenerated my code", "which RTOS pattern should I use", "MPU fault", "watchdog keeps resetting", "which protocol should I use for my sensor", "ESP32 deep sleep", "PSRAM vs DRAM", "ESP32 heap keeps shrinking", "ESP.getFreeHeap()", "task stack overflow on ESP32", or "WiFi reconnect after deep sleep is slow".
Design partition schemes, select partition keys, create GSI, and write SQL for PolarDB-X 2.0 Enterprise Edition AUTO mode databases, handling PolarDB-X vs MySQL differences (partitioned tables, GSI, CCI, Sequence, table groups, TTL, pagination, etc.). Use when designing partition schemes, selecting partition keys, converting single tables to partitioned tables, creating GSI/CCI indexes, writing or migrating SQL for PolarDB-X, or diagnosing slow queries on PolarDB-X. Triggers: "PolarDB-X SQL", "PolarDB-X create table", "partitioned table", "partition design", "partition scheme", "partition key", "GSI", "CCI", "Sequence", "MySQL migrate to PolarDB-X", "PolarDB-X compatibility", "single table to partitioned table", "convert to partitioned table", "large table", "distributed table", "AUTO mode", "pagination query", "Keyset pagination", "Range partition", "auto add partition", "PolarDB-X slow query", "full-shard scan"
Prevent Ethereum hashing bugs in JavaScript and TypeScript. Node's sha3-256 is NIST SHA3, not Ethereum Keccak-256, and silently breaks selectors, signatures, storage slots, and address derivation.
Audit and improve SwiftUI runtime performance from code review and architecture. Use for requests to diagnose slow rendering, janky scrolling, high CPU/memory usage, excessive view updates, or layout thrash in SwiftUI apps, and to provide guidance for user-run Instruments profiling when code review alone is insufficient.
Apply Hierarchical Linear Modeling (HLM) to analyze nested data structures with random intercepts and slopes, accounting for intra-class correlation and cross-level interactions. Use this skill when the user has students nested in schools, employees in firms, or repeated measures in individuals, needs to partition variance across levels, or when they ask 'how do I handle nested data', 'what is ICC', or 'do group-level factors moderate individual-level relationships'.
Write, validate, and optimise PromQL queries for Prometheus and Grafana Cloud Metrics. Use when the user asks to query metrics, write a PromQL expression, calculate rates, aggregate across labels, build histogram quantiles, create recording rules, debug query performance, or understand metric cardinality. Triggers on phrases like "PromQL", "Prometheus query", "write a metric query", "calculate rate", "histogram_quantile", "recording rule", "metric cardinality", "sum by", "rate vs irate", "absent()", or "query is slow".
When the user wants to optimize picker routes, minimize travel distance in warehouses, or improve picking efficiency. Also use when the user mentions "pick path optimization," "warehouse routing," "travel distance minimization," "TSP in warehouses," "S-shape routing," or "optimal pick sequence." For order batching, see order-batching-optimization. For warehouse slotting, see warehouse-slotting-optimization.
Aggressively clean up a codebase by removing AI slop, dead code, weak types, defensive over-engineering, duplication, and legacy cruft. Orchestrates 8 specialized subagents in parallel to deduplicate code, consolidate types, kill unused code, untangle circular dependencies, strengthen weak types, remove unnecessary try/catch, delete deprecated/legacy paths, and strip unhelpful comments. Use when the user asks to 'clean up the codebase', 'remove slop', 'improve code quality', 'remove dead code', 'kill AI slop', 'tighten types', 'remove legacy code', 'deduplicate code', 'DRY this up', 'untangle dependencies', or wants a thorough code quality pass. Also use when the user mentions code smells, technical debt cleanup, or refactoring for clarity — even if they don't use the word 'slop'.
MUST be used whenever optimizing a Dune app for speed, reducing render counts, improving CDF query efficiency, or reducing bundle size. Do NOT skip measurement steps — always profile before changing code. Triggers: performance, slow, laggy, optimize, optimization, re-render, bundle size, load time, Lighthouse, profiler, virtualization, lazy load, code split, CDF query, large list, memory leak.