Total 30,804 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
The market analysis function of Gate Exchange — liquidity, momentum, liquidation, funding arbitrage, basis, manipulation risk, order book explainer, slippage simulation. Use when the user asks about liquidity, depth, slippage, buy/sell pressure, liquidation, funding rate arbitrage, basis/premium, manipulation risk, order book explanation, or slippage simulation (e.g. market buy $X slippage). Trigger phrases: liquidity, depth, slippage, momentum, buy/sell pressure, liquidation, squeeze, funding rate, arbitrage, basis, premium, manipulation, order book, spread, slippage simulation.
Trend and technical analysis. Use this skill whenever the user asks for technical or trend analysis of one coin. Trigger phrases include: technical analysis, K-line, RSI, MACD, trend, support, resistance. MCP tools: info_markettrend_get_kline, info_markettrend_get_indicator_history, info_markettrend_get_technical_analysis, info_marketsnapshot_get_market_snapshot.
Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
Perform RFM (Recency, Frequency, Monetary) customer segmentation analysis on e-commerce data. Use when you need to analyze customer value, identify VIP customers, or create marketing segments. Automatically cleans data, calculates RFM metrics, applies K-means clustering, and generates visualization reports with Chinese language support.
SQL query expert for optimization, schema design, and data analysis
Execute ES|QL (Elasticsearch Query Language) queries, use when the user wants to query Elasticsearch data, analyze logs, aggregate metrics, explore data, or create charts and dashboards from ES|QL results.
Ingest and transform data files (CSV/JSON/Parquet/Arrow IPC) into Elasticsearch with stream processing, custom transforms, and cross-version reindexing. Use when loading files, batch importing data, or migrating indices across versions — not for general ingest pipeline design or bulk API patterns.
Create and manage Kibana Dashboards and Lens visualizations. Use when you need to define dashboards and visualizations declaratively, version control them, or automate their deployment.
🔍 Find API | 寻找可靠数据源 TRIGGERS: Use when agent needs to fetch external data, user mentions "reliable data source", "数据源", "API", or when web scraping is inefficient/inaccurate. A comprehensive guide to reliable data APIs across all domains. Helps agents find the best APIs instead of inefficient web scraping. Currently covers: Stock/Financial data, Weather, News, Maps, and more domains coming soon. 触发条件：Agent 需要获取外部数据、用户提到"可靠数据源"、"数据源"、"API"，或网页爬取效率低/不准确时。 跨领域可靠数据 API 的综合指南。 帮助 Agent 找到最佳 API，避免低效的网页爬取。 目前覆盖：股票/金融数据、天气、新闻、地图，更多领域持续完善中。
Write SQL, TypeScript, and dynamic table transforms for Goldsky Turbo pipelines. Use this skill for: decoding EVM event logs with _gs_log_decode (requires ABI) or transaction inputs with _gs_tx_decode, filtering and casting blockchain data in SQL, combining multiple decoded event types into one table with UNION ALL, writing TypeScript/WASM transforms using the invoke(data) function signature, setting up dynamic lookup tables to filter transfers by a wallet list you update at runtime (dynamic_table_check), chaining SQL and TypeScript steps together, or debugging null values in decoded fields. For full pipeline YAML structure, use /turbo-pipelines instead. For building an entire pipeline end-to-end, use /turbo-builder instead.
Goldsky Turbo pipeline YAML reference — the authoritative source for field names, required vs optional fields, and valid values. Use whenever the user asks about specific YAML fields: what does `start_at: earliest` vs `latest` do, what fields does a postgres/clickhouse/kafka sink require, what is the `from:` field in a sink, how does `checkpoint` work, what's the syntax for `batch_size` or `primary_key`. Also use for validation errors like 'unknown field' or 'missing required field'. For interactive pipeline building end-to-end, use /turbo-builder instead.