Total 54,360 skills, Data Processing has 2781 skills
Showing 12 of 2781 skills
Install and verify cuPyNumeric for Python — requirements, commands, verification. Source builds are out of scope.
Crypto social sentiment, news, influencer tracking, and topic intelligence. Use when gauging crowd mood, tracking KOL posts, or finding news on a coin (e.g. SOL sentiment, who's posting about $PEPE, AI category trend).
Render and extract web page content via AceDataCloud's WebExtrator API. Use when scraping a page's final rendered HTML, or extracting typed structured data (Article, Product, Recipe, Video, Discussion, Job) plus clean markdown/text from any URL. Real headless Chromium with schema.org + LLM extraction.
Track data lineage and provenance from source to consumption. Use when auditing data flows, debugging data quality issues, ensuring compliance (GDPR, SOX), or understanding data dependencies. Covers lineage tracking, impact analysis, data catalogs, and metadata management.
Set up real-time indicator computation on live WebSocket market data. Streams LTP/Quote/Depth and computes indicators in real-time with optional Plotly live charting.
Is this token held by quality wallets or retail noise? SM holder ratio, flow breakdown by label, and recent buyer quality.
Use this skill any time the user wants to analyze data, create charts, or build data visualizations. This includes: sales analysis, financial modeling, cohort analysis, funnel analysis, A/B test results, KPI tracking, data reports, revenue breakdowns, user retention analysis, conversion rate analysis, CSV summarization, and dashboard creation. Also trigger when: user says 分析这组数据, 做个图表, 数据可视化, 销售分析, 漏斗分析, 留存分析, 做个数据报表. If data needs to be analyzed or visualized, use this skill.
This skill should be used when users need to scrape content from websites, extract text from web pages, crawl and follow links, or download documentation from online sources. It features concurrent URL processing, automatic deduplication, content filtering, domain restrictions, and proper directory hierarchy based on URL structure. Use for documentation gathering, content extraction, web archival, or research data collection.
Bitcoin bottom-timing judgment model. By tracking 6 core indicators (RSI technical oversold, volume dry-up, MVRV ratio, social media fear index, miner shutdown price, long-term holder behavior), it comprehensively evaluates whether Bitcoin has entered a bottom-fishing zone and outputs a bottom-fishing rating and position-building recommendations. When users mention topics such as Bitcoin bottom-fishing, whether BTC has bottomed out, Bitcoin oversold, MVRV, miner shutdown price, long-term holder LTH, Bitcoin fear index, whether to buy Bitcoin, BTC position entry timing, crypto market bottom signals, Bitcoin cycle bottom, etc., be sure to use this skill. Even if the user simply asks "Can I buy the dip on Bitcoin now?" or "Has BTC finished dropping?", this skill should be triggered to provide a structured analysis framework.
Decision-first data analysis with statistical rigor gates. Use when analyzing CSV, JSON, database exports, API responses, logs, or any structured data to support a business decision. Handles: trend analysis, cohort comparison, A/B test evaluation, distribution profiling, anomaly detection. Do NOT use for codebase analysis (use codebase-analyzer), codebase exploration (use explore-pipeline), or ML model training.
Fetch the latest financial signals and transmission-chain analyses from DeepEar Lite. Use when the user needs immediate insights into financial market trends, stock performance factors, and reasoning from the DeepEar Lite dashboard.
Design and operate reconciliation processes that ensure data accuracy across portfolio management custodian and clearing systems. Use when building or evaluating a daily position cash or transaction reconciliation process, investigating discrepancies between internal systems and custodian records, diagnosing recurring break patterns especially from corporate actions or pricing differences, setting tolerance thresholds for position cash or market value matching, implementing three-way reconciliation across advisor system custodian and clearing firm, designing break investigation workflows with aging and escalation, normalizing data across multi-custodian feeds from Schwab Fidelity or Pershing, reconciling cost basis tax lots or accrued income across systems, evaluating reconciliation platforms like Arcesium Duco or Advent Geneva, or preparing for regulatory examinations on books and records accuracy.