Total 50,523 skills, Data Processing has 2561 skills
Showing 12 of 2561 skills
Is this token held by quality wallets or retail noise? SM holder ratio, flow breakdown by label, and recent buyer quality.
US stock market sentiment monitoring and position recommendation system. Evaluates market sentiment by tracking 5 core indicators (NAAIM Exposure Index, Institutional Equity Allocation, Retail Net Buying, S&P 500 Forward P/E Ratio, Hedge Fund Leverage) and outputs sentiment ratings and position recommendations. This skill should be used when the user mentions topics such as US stock sentiment, market overheating, greed/fear indicators, NAAIM, institutional positioning, retail sentiment, P/E valuation bubbles, hedge fund leverage, whether to reduce positions, market risk assessment, position management advice, market top/bottom signals, etc. Even if the user simply asks "Is the US stock market risky right now?" or "Should I reduce my positions?", this skill should be triggered to provide a structured analytical framework.
Use this skill when implementing data validation, data quality monitoring, data lineage tracking, data contracts, or Great Expectations test suites. Triggers on schema validation, data profiling, freshness checks, row-count anomalies, column drift, expectation suites, contract testing between producers and consumers, lineage graphs, data observability, and any task requiring data integrity enforcement across pipelines.
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.
Build Airflow 3.1+ plugins that embed FastAPI apps, custom UI pages, React components, middleware, macros, and operator links directly into the Airflow UI. Use this skill whenever the user wants to create an Airflow plugin, add a custom UI page or nav entry to Airflow, build FastAPI-backed endpoints inside Airflow, serve static assets from a plugin, embed a React app in the Airflow UI, add middleware to the Airflow API server, create custom operator extra links, or call the Airflow REST API from inside a plugin. Also trigger when the user mentions AirflowPlugin, fastapi_apps, external_views, react_apps, plugin registration, or embedding a web app in Airflow 3.1+. If someone is building anything custom inside Airflow 3.1+ that involves Python and a browser-facing interface, this skill almost certainly applies.
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.
Salesforce Data Cloud Act phase. TRIGGER when: user manages activations, activation targets, data actions, or downstream delivery of Data Cloud audiences and data. DO NOT TRIGGER when: the task is segment creation (use sf-datacloud-segment), data retrieval/search work (use sf-datacloud-retrieve), or STDM/session tracing (use sf-ai-agentforce-observability).
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).
Global Comprehensive Stock Analysis Tool. Supports all markets covered by Eastmoney, including A-shares, Hong Kong stocks, US stocks, etc. Based on the stock name or code entered by users, it obtains stock information from Eastmoney.com, conducts three-dimensional analysis of fundamentals, news, and capital flows, and provides investment suggestions, buy prices and sell prices. Trigger keywords: analyze stocks, stock recommendations, stock entry and exit points, stock research, A-share analysis, Hong Kong stock analysis, US stock analysis, Chinese concept stocks, Hang Seng Index, Nasdaq, S&P 500, Dow Jones, Tencent, Alibaba, Apple AAPL, Tesla TSLA, NVIDIA NVDA, Micron MU, etc.
Comprehensive SAC scripting skill for SAP Analytics Cloud Analytics Designer and Optimized Story Experience. This skill should be used when the user asks to "create SAC script", "debug Analytics Designer", "optimize SAC performance", "planning operations in SAC", "filter data in SAC", "use DataSource API", "chart scripting", "table manipulation", "SAC event handlers", "version management", "data locking", "Optimized Story Experience API", "OSE scripting", "OSE widget API", "OSE DataSource", "story scripting API", "OSE planning API", "OSE method", "optimized story", "SAC story scripting", "story script", "SAC scripting", or works with SAC widgets, planning models, or analytics applications.
Assess data quality with checks for missing values, duplicates, type issues, and inconsistencies. Use for data validation, ETL pipelines, or dataset documentation.
Create an Extruct company table from user-provided data, upload rows, and optionally add enrichment columns. Handles the full flow: parse input (CSV, pasted list, or structured data), create or reuse a table, upload domains in batches, add agent columns, and trigger enrichment. Triggers on: "create table", "upload companies", "add to extruct", "new extruct table", "import companies", "upload list to extruct".