Total 55,032 skills, Data Processing has 2818 skills
Showing 12 of 2818 skills
Help users write correct R code for async, parallel, and distributed computing using mirai. Use when users need to: run R code asynchronously or in parallel, write mirai code with correct dependency passing, set up local or remote parallel workers, convert code from future or parallel, use parallel map operations, integrate async tasks with Shiny or promises, or configure cluster/HPC computing.
Generate a one-page Market Posture summary with net exposure ceiling, growth-vs-value bias, participation breadth, and new-entry-allowed vs cash-priority recommendation by integrating signals from breadth, regime, and flow analysis skills.
Sets up and operates Airbyte Agent Connectors — strongly typed Python packages for accessing 51+ third-party SaaS APIs through a unified entity-action interface. Supported services include Salesforce, HubSpot, Stripe, GitHub, Slack, Jira, Shopify, Zendesk, Google Ads, Notion, Linear, Intercom, Gong, and 36 more connectors spanning CRM, billing, payments, e-commerce, marketing, analytics, project management, helpdesk, developer tools, HR, and communication platforms. Make sure to use this skill when the user wants to connect to any SaaS API, install an airbyte-agent connector package, integrate third-party service data into a Python application or AI agent, query or search records from any supported service, or configure Airbyte MCP tools for Claude. Covers Platform Mode (Airbyte Cloud) and OSS Mode (local Python SDK).
Financial time series analysis method toolkit. Covers stocks / commodity futures / cryptocurrencies / ETFs / foreign exchange / indices, full process from data acquisition to high-level analysis. Built-in 70+ analysis methods, covering 8 major method domains: time series testing, predictive modeling, cross-asset relationships, volatility risk, portfolio optimization, state recognition, commodity-specific analysis and network analysis. Tushare MCP tool (A shares/Hong Kong stocks/US stocks/futures/funds/macro) is preferred for data acquisition, and yfinance scripts are used to supplement assets not covered by tushare such as commodity futures (CL=F) and crypto (BTC-USD).
Mathematical visualization skill for equations, proofs, and geometric concepts. **Triggers when:** - User mentions equations, formulas, or mathematical expressions - Request involves mathematical proofs or derivations - Content includes geometric relationships - User mentions LaTeX, calculus, algebra, geometry, trigonometry - Patterns: "equation", "formula", "prove", "derive", "graph", "plot" **Capabilities:** - LaTeX equation rendering with color-coded components - Function graphing and transformations - Geometric constructions and proofs - 3D mathematical surfaces - Step-by-step derivations with highlights
Plans new DataHub connectors by classifying the source system, researching it using a dedicated agent or inline research, and generating a _PLANNING.md blueprint with entity mapping and architecture decisions. Use when building a new connector, researching a source system for DataHub, or designing connector architecture. Triggers on: "plan a connector", "new connector for X", "research X for DataHub", "design connector for X", "create planning doc", or any request to plan/research/design a DataHub ingestion source.
CRM data quality, deduplication, enrichment automation, record matching, and data decay management. Use when cleaning CRM data, deduplicating contacts or accounts, fixing stale records, setting up auto-enrichment workflows, normalizing job titles or industries, auditing data quality, or managing data decay. Do NOT use for one-time enrichment of a prospect list (use /sales-enrich), building new prospect lists (use /sales-prospect-list), or ZoomInfo-specific config (use /sales-zoominfo). For platform-specific help, use /sales-zoominfo.
Brainstorm football data visualisations and chart designs. Use when the user wants ideas for how to visualise football data, needs inspiration for chart types, wants to explore design approaches for match reports, player profiles, team dashboards, or any football analytics graphic. Searches the web for popular approaches and real-world examples before proposing options.
Metabase integration. Manage data, records, and automate workflows. Use when the user wants to interact with Metabase data.
Build search applications and query log analytics data with OpenSearch. Use this skill when the user mentions OpenSearch, search app, index setup, search architecture, semantic search, vector search, hybrid search, BM25, dense vector, sparse vector, agentic search, RAG, embeddings, KNN, PDF ingestion, document processing, or any related search topic. Also use for log analytics and observability — when the user wants to set up log ingestion, query logs with PPL, analyze error patterns, set up index lifecycle policies, investigate traces, or check stack health. Activate even if the user says log analysis, Fluent Bit, Fluentd, Logstash, syslog, traceId, OpenTelemetry, or log analytics without mentioning OpenSearch.
Qualetics integration. Manage data, records, and automate workflows. Use when the user wants to interact with Qualetics data.
ETF analysis framework via Longbridge — product screening (AUM/expense ratio/index), tracking error, liquidity (bid-ask spread/volume), premium/discount (NAV vs market price), and A-share ETF allocation insights. Triggers: "ETF分析", "ETF选择", "ETF跟踪误差", "ETF溢价", "ETF流动性", "ETF费率", "ETF规模", "宽基ETF", "行业ETF", "指数基金", "ETF分析", "ETF選擇", "ETF追蹤誤差", "ETF溢價", "ETF流動性", "ETF費率", "ETF規模", "指數基金", "ETF analysis", "ETF selection", "tracking error", "ETF premium discount", "ETF liquidity", "expense ratio", "broad market ETF", "sector ETF", "index fund".