Total 54,903 skills, Data Processing has 2816 skills
Showing 12 of 2816 skills
Design and architect Goldsky Turbo pipelines. Use this skill for 'should I use X or Y' decisions: kafka source vs dataset source, streaming vs job mode, which resource size (xs/s/m/l/xl/xxl) for my workload, postgres vs clickhouse vs kafka sink, fan-in vs fan-out data flow, one pipeline vs many, dynamic table vs SQL join, how to handle multi-chain deployments. Also use when the user asks 'what's the best way to...' for a pipeline design problem, or is unsure how to structure their pipeline before building it.
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.
Re-parse the currently open ScienceDirect search results page. Internal skill used by other skills.
Web crawling and scraping tool with LLM-optimized output. 网页爬虫爬取工具 | Web crawler, web scraper, spider. DuckDuckGo search, site crawling, dynamic page scraping. 智能搜索爬取 | Free, no API key required.
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.
A Tushare data research skill for Chinese natural language. It converts requests like "How has this stock been performing lately?", "Help me check the financial report trend", "Which sector is the strongest recently?", "What are northbound funds buying?", "Export a market data report for me" into executable workflows for data acquisition, cleaning, comparison, filtering, export, and brief analysis. It applies to research scenarios such as A-shares, indices, ETFs/funds, finance, valuation, capital flows, announcements & news, sector concepts, and macroeconomic data.
Assess data quality with checks for missing values, duplicates, type issues, and inconsistencies. Use for data validation, ETL pipelines, or dataset documentation.
Extract competitor and customer intelligence from any company's landing page HTML. Discovers tech stack, analytics tools, ad pixels, customer logos, SEO metadata, CTAs, hidden elements, and more. No API keys required.
Discover all customers of a given company by scanning websites, case studies, review sites, press, social media, job postings, and more. Use when you need competitive intelligence on who a company sells to.
Use this skill for XCrawl crawl tasks, including bulk site crawling, crawler rule design, async status polling, and delivery of crawl output for downstream scrape and search workflows.
Overview The Google Maps Agent transforms geographical and local business data into structured, actionable intelligence. It allows users to extract data from Google Maps to audit local markets, monito
Aggregate and rank signals from multiple edge-finding skills (edge-candidate-agent, theme-detector, sector-analyst, institutional-flow-tracker) into a prioritized conviction dashboard with weighted scoring, deduplication, and contradiction detection.