Total 50,523 skills, Data Processing has 2561 skills
Showing 12 of 2561 skills
Firecrawl web scraping API via curl. Use this skill to scrape webpages, crawl websites, discover URLs, search the web, or extract structured data.
Apply Web Scraping with Python practices (Ryan Mitchell). Covers First Scrapers (Ch 1: urllib, BeautifulSoup), HTML Parsing (Ch 2: find, findAll, CSS selectors, regex, lambda), Crawling (Ch 3-4: single-domain, cross-site, crawl models), Scrapy (Ch 5: spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams, Markov, NLTK), Forms & Logins (Ch 10: POST, sessions, cookies), JavaScript (Ch 11: Selenium, headless, Ajax), APIs (Ch 12: REST, undocumented), Image/OCR (Ch 13: Pillow, Tesseract), Avoiding Traps (Ch 14: headers, honeypots), Testing (Ch 15: unittest, Selenium), Parallel (Ch 16: threads, processes), Remote (Ch 17: Tor, proxies), Legalities (Ch 18: robots.txt, CFAA, ethics). Trigger on "web scraping", "BeautifulSoup", "Scrapy", "crawler", "spider", "scraper", "parse HTML", "Selenium scraping", "data extraction".
彙整今日中國宏觀經濟新聞消息，從華爾街日報、36氪等來源抓取並篩選宏觀相關新聞，輸出雜誌風格的新聞摘要。適用於交易/研究開盤前快速掌握中國宏觀動態。
Arquiteto de Dados especialista em PostgreSQL, Supabase e modelagem multi-tenant para a plataforma PAPO
Data format specialist covering TOON encoding, JSON/YAML optimization, serialization patterns, and data validation for modern applications. Use when optimizing data for LLM transmission, implementing high-performance serialization, validating data schemas, or converting between data formats.
Query Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team performance, PR/code review metrics, deployment frequency, incident data, AI tool adoption, survey responses, DORA metrics, or any engineering analytics. Triggers on questions about DX scores, team comparisons, cycle times, code quality, developer sentiment, AI coding assistant adoption, sprint velocity, or engineering KPIs.
Bitquery integration. Manage data, records, and automate workflows. Use when the user wants to interact with Bitquery data.
When the user wants to optimize inventory levels, calculate safety stock, determine reorder points, or minimize inventory costs. Also use when the user mentions "inventory management," "safety stock," "EOQ," "reorder point," "service level," "stockout prevention," "ABC analysis," "inventory turns," or "working capital reduction." For warehouse slotting, see warehouse-slotting-optimization. For multi-echelon systems, see multi-echelon-inventory.
When the user wants to optimize energy supply chains, coordinate oil and gas logistics, or manage energy infrastructure. Also use when the user mentions "energy transportation," "pipeline management," "energy distribution," "oil and gas supply chain," "LNG logistics," "petroleum logistics," "energy asset management," or "energy infrastructure." For renewable energy, see renewable-energy-planning. For power grids, see power-grid-optimization.
Create data analytics and data pipeline diagrams using PlantUML syntax with analytics/database stencil icons. Best for ETL pipelines, data lakes, real-time streaming, data warehousing, and BI dashboards. NOT for simple flowcharts (use mermaid) or general cloud infra (use cloud skill).
Apply meta-analysis to synthesize effect sizes across multiple studies, assess heterogeneity, and evaluate publication bias. Use this skill when the user needs to combine findings from prior research, compare fixed-effect vs random-effects models, compute pooled effect sizes, or when they ask 'what does the overall evidence say', 'how do I combine results across studies', or 'is there publication bias'.
Conduct cohort analysis to track user behavior over time, build retention matrices, and compare cohort performance. Use this skill when the user needs to measure retention, understand how user behavior changes after acquisition, compare product versions' impact on engagement, or predict LTV — even if they say 'what's our retention rate', 'are newer users behaving differently', 'build a retention table', or 'how long do customers stick around'.