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Found 1,230 Skills
Full Sentry SDK setup for PHP. Use when asked to "add Sentry to PHP", "install sentry/sentry", "setup Sentry in PHP", or configure error monitoring, tracing, profiling, logging, metrics, or crons for PHP applications. Supports plain PHP, Laravel, and Symfony.
DevOps and IT Ops automation - CI/CD, monitoring, incident management, and infrastructure workflows
Full Sentry SDK setup for Go. Use when asked to "add Sentry to Go", "install sentry-go", "setup Sentry in Go", or configure error monitoring, tracing, logging, metrics, or crons for Go applications. Supports net/http, Gin, Echo, Fiber, FastHTTP, Iris, and Negroni.
Monitor LLMs and agentic apps: performance, token/cost, response quality, and workflow orchestration. Use when the user asks about LLM monitoring, GenAI observability, or AI cost/quality.
Full Sentry SDK setup for Cloudflare Workers and Pages. Use when asked to "add Sentry to Cloudflare Workers", "install @sentry/cloudflare", or configure error monitoring, tracing, logging, crons, or AI monitoring for Cloudflare Workers, Pages, Durable Objects, Queues, Workflows, or Hono on Cloudflare.
US stock market sentiment monitoring and position recommendation system. Evaluates market sentiment by tracking 5 core indicators (NAAIM Exposure Index, Institutional Equity Allocation, Retail Net Buying, S&P 500 Forward P/E Ratio, Hedge Fund Leverage) and outputs sentiment ratings and position recommendations. This skill should be used when the user mentions topics such as US stock sentiment, market overheating, greed/fear indicators, NAAIM, institutional positioning, retail sentiment, P/E valuation bubbles, hedge fund leverage, whether to reduce positions, market risk assessment, position management advice, market top/bottom signals, etc. Even if the user simply asks "Is the US stock market risky right now?" or "Should I reduce my positions?", this skill should be triggered to provide a structured analytical framework.
This skill should be used when the user asks for 'TRX price', 'TRON token price', 'price chart on TRON', 'K-line data for USDT/TRX', 'TRON trade history', 'TRON whale activity', 'large transfers on TRON', 'smart money on TRON', 'TRON DEX volume', or mentions checking real-time prices, candlestick data, trading volume, whale monitoring, or smart money signals on the TRON network. For token search and metadata, use tron-token. For swap execution, use tron-swap.
INVOKE THIS SKILL for LLM-as-judge evaluation workflows on Arize: creating/updating evaluators, running evaluations on spans or experiments, tasks, trigger-run, column mapping, and continuous monitoring. Use when the user says: create an evaluator, LLM judge, hallucination/faithfulness/correctness/relevance, run eval, score my spans or experiment, ax tasks, trigger-run, trigger eval, column mapping, continuous monitoring, query filter for evals, evaluator version, or improve an evaluator prompt.
Use when you need to implement or improve Java logging and observability — including selecting SLF4J with Logback/Log4j2, applying proper log levels (ERROR, WARN, INFO, DEBUG, TRACE), parameterized logging, secure logging without sensitive data exposure, environment-specific configuration, log aggregation and monitoring, or validating logging through tests. Part of the skills-for-java project
Real-time multi-chain gas monitoring and spike detection. Monitors block-by-block gas prices, detects sudden spikes, identifies gas war culprits, and alerts when significant price increases occur. Sup
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Monitor background processes from Claude Code using sentinel files, heartbeat liveness, and subagent polling. Best practices and anti-patterns for autonomous loops that need to kick off work, detect completion/failure/hang/timeout, and resume the main context without wasting tokens. TRIGGERS - monitor background process, sentinel file, heartbeat monitoring, process supervision, agentic loop monitor, background task health, detect hung process, poll for completion, watchdog pattern, process liveness, monitor long-running task, agent poll loop, circuit breaker pattern.