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Found 667 Skills
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
Overview The X Agent mpowers businesses, researchers, and marketers to move beyond surface-level monitoring to gain a comprehensive understanding of brand sentiment, competitor strategies, and communi
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
Find, connect, and use MCP tools and skills via the Smithery CLI. Use when the user searches for new tools or skills, wants to discover integrations, connect to an MCP, install a skill, or wants to interact with an external service (email, Slack, Discord, GitHub, Jira, Notion, databases, cloud APIs, monitoring, etc.).
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.
Postmark platform help — transactional email delivery via REST API (`POST /email`, `POST /email/batch`), SMTP relay, Message Streams (transactional vs broadcast isolation), Handlebars Templates with layout inheritance, Inbound Email parsing, Webhooks (bounce, delivery, open, click, spam complaint, subscription change, inbound), DMARC Monitoring, Bounce Management (Rebound), Suppressions, Statistics, Bulk API, Sender Signatures, and domain authentication. Use when asking 'how do I do X in Postmark', sending transactional email with Postmark, configuring Message Streams, setting up Postmark templates, processing inbound email via Postmark, managing bounces and suppressions, or troubleshooting Postmark deliverability. Do NOT use for general email marketing strategy (use /sales-email-marketing), cross-platform email deliverability (use /sales-deliverability), email open/click tracking strategy (use /sales-email-tracking), or SendGrid-specific questions (use /sales-sendgrid).
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.
Use when the user wants to analyze EKS application logs during or after a FIS experiment. Triggers on "analyze app logs", "application log analysis", "check application behavior", "分析应用日志", "查看应用表现", "应用日志分析". Supports two modes: real-time monitoring (during experiment) and post-hoc analysis (after experiment). Reads experiment context from aws-fis-experiment-prepare/execute outputs.
Track and analyze Amazon keyword rankings. Set up rank monitoring workflows, interpret ranking changes, and develop strategies to improve organic search position.