Total 53,169 skills, Data Processing has 2676 skills
Showing 12 of 2676 skills
Track macroeconomic events, Fed rates, CPI, and economic indicators affecting crypto.
Review fixed income portfolios by pricing multiple bonds, retrieving reference data, analyzing cashflows, and running scenario analysis. Use when reviewing bond portfolios, computing portfolio duration and DV01, analyzing cashflow waterfalls, stress testing rate scenarios, or assessing portfolio composition.
Create advanced Excel pivot tables with calculated fields and slicers. Use when building data summaries or creating interactive dashboards. Trigger with phrases like 'excel pivot', 'create pivot table', 'data summary'.
OpenSearch development best practices for indexing, querying, search optimization, vector search, and cluster management
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.
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.
Assemble multi-panel scientific figures with panel labels (A, B, C) at publication quality (300 DPI) using R. Use when combining individual plots into journal-ready figures.
Use this skill when building real-time data pipelines, stream processing jobs, or change data capture systems. Triggers on tasks involving Apache Kafka (producers, consumers, topics, partitions, consumer groups, Connect, Streams), Apache Flink (DataStream API, windowing, checkpointing, stateful processing), event sourcing implementations, CDC with Debezium, stream processing patterns (windowing, watermarks, exactly-once semantics), and any pipeline that processes unbounded data in motion rather than data at rest.
Control which data each viewer sees in an embedded Domo dashboard/card via server-side programmatic filters and dataset switching. Covers the OAuth → embed token flow, standard filters, SQL filters (OR/BETWEEN/LIKE), per-dataset targeting, datasetRedirects for multi-tenant architectures, and token size limits. Use for any per-viewer, per-role, or per-tenant data restrictions at embed time. Not for client-side JS API filtering (use cap-de-jsapi-filters).
Use this skill for XCrawl search tasks, including keyword search request design, location and language controls, result analysis, and follow-up crawl or scrape planning.
Fetch financial data from the Funda AI API (https://api.funda.ai). Covers quotes, historical prices, financials, SEC filings, earnings transcripts, analyst estimates, options flow/greeks/GEX, supply chain graph, social sentiment, prediction markets, congressional trades, economic indicators, ESG, and news. Triggers: stock quotes, fundamentals, balance sheet, income statement, cash flow, analyst targets, DCF, options chain/flow/unusual activity, GEX, IV rank, max pain, earnings/dividend/IPO calendar, SEC filings (10-K/10-Q/8-K), transcripts, supply chain (suppliers/customers/competitors), congressional trading, insider trades, institutional holdings (13F), Reddit/Twitter sentiment, Polymarket, treasury rates, GDP, CPI, FRED data, ESG scores, commodity/forex/crypto prices, stock screener, sector performance, ETF holdings, news, COT reports. Also triggers for "funda" or "funda.ai". If only a ticker is provided and Funda API can answer, use this skill.
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.