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Found 878 Skills
Provides NodeReal MegaNode blockchain infrastructure APIs for 25+ chains including BSC, Ethereum, opBNB, Optimism, Polygon, Arbitrum, and Klaytn. Covers standard JSON-RPC endpoints, Enhanced APIs (nr_ methods for ERC-20 token balances, NFT holdings, asset transfers), MegaFuel gasless transactions via BEP-322 paymaster, Direct Route MEV protection, Debug/Trace APIs, WebSocket subscriptions, ETH Beacon Chain consensus layer, Portal API usage monitoring, API Marketplace (NFTScan, Contracts API, SPACE ID, Greenfield, BNB Staking, PancakeSwap, zkSync), non-EVM chains (Aptos, NEAR, Avalanche), and JWT authentication. Use when building blockchain dApps with NodeReal, querying token or NFT data, setting up RPC infrastructure, configuring gasless transactions, protecting against MEV, tracing transactions, verifying smart contracts, resolving .bnb domains, or monitoring validators and API usage.
Browser automation skill that supports 101 tools, including page navigation, element interaction, content extraction, screenshot capture, network control, performance monitoring and more
Use this skill when diagnosing, configuring, or monitoring NICs for AF_XDP / XDP workloads. Covers driver detection, hardware queue configuration, offload control (GSO/GRO/TSO/LRO), VLAN offloads, Flow Director (FDIR) rules, CPU core pinning and NUMA awareness, hardware queue and drop monitoring, BPF program inspection with bpftool, kernel tracing via ftrace, perf profiling and flamegraphs, IRQ-to-queue-to-core mapping, and a quick diagnostic checklist.
Use this skill when diagnosing, configuring, or monitoring NICs for AF_XDP / XDP workloads. Covers driver detection, hardware queue configuration, ring buffer sizing, RSS indirection table management, interrupt coalesce tuning, offload control (GSO/GRO/TSO/LRO), VLAN offloads, Flow Director (FDIR) rules with loc pinning and ixgbe wipe bug workaround, RPS/XPS queue CPU mapping, sysctl network tuning, CPU core pinning and NUMA awareness, hardware queue and drop monitoring, softirq and rx_missed_errors analysis, BPF program inspection with bpftool (prog dump xlated, net show), kernel tracing via ftrace and dmesg, perf profiling and flamegraphs, IRQ-to-queue-to-core mapping, bonding interface diagnostics, socket inspection, and a quick diagnostic checklist.
Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.
Conduct Failure Mode and Effects Analysis (FMEA) for systematic identification and risk assessment of potential failures in designs, processes, or systems. Supports DFMEA (Design), PFMEA (Process), and FMEA-MSR (Monitoring & System Response). Uses AIAG-VDA 7-step methodology with Action Priority (AP) risk assessment replacing traditional RPN. Use when analyzing product designs for potential failures, evaluating manufacturing process risks, conducting proactive risk assessment, preparing for APQP/PPAP submissions, investigating field failures, or when user mentions "FMEA", "failure mode", "DFMEA", "PFMEA", "severity occurrence detection", "RPN", "Action Priority", "design risk analysis", or needs to identify and prioritize potential failure modes with their causes and effects.
Extract structured data from multiple web pages using Playwright with built-in ethical crawling practices including rate limiting, robots.txt compliance, and error monitoring. Use when asked to "scrape data from", "extract information from pages", "collect data from site", "crawl multiple pages", or when gathering structured data from websites. Supports pagination, multi-page extraction, data aggregation, and export to CSV/JSON/Markdown. Works with browser_navigate, browser_evaluate, browser_wait_for, and browser_snapshot tools.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Delegate complex coding tasks to OpenCode agent. Use when building new features, reviewing code, or refactoring large codebases. Allows starting, resuming, and monitoring opencode sessions.
Instrument, trace, evaluate, and monitor LLM applications and AI agents with LangSmith. Use when setting up observability for LLM pipelines, running offline or online evaluations, managing prompts in the Prompt Hub, creating datasets for regression testing, or deploying agent servers. Triggers on: langsmith, langchain tracing, llm tracing, llm observability, llm evaluation, trace llm calls, @traceable, wrap_openai, langsmith evaluate, langsmith dataset, langsmith feedback, langsmith prompt hub, langsmith project, llm monitoring, llm debugging, llm quality, openevals, langsmith cli, langsmith experiment, annotate llm, llm judge.
System administration expert for Linux, macOS, Windows, services, and monitoring
Supervise and manage an inner Claude Code instance running in tmux. Use this skill when you need to delegate implementation work to an inner Claude while focusing on task planning, progress monitoring, and end-to-end acceptance testing. Ideal for long-running tasks that would otherwise exhaust a single Claude's context window.