Total 54,475 skills, Data Processing has 2787 skills
Showing 12 of 2787 skills
Fetch web page content via Chrome DevTools Protocol (CDP). Full JS rendering, handles redirects (including Google News). Use when you need to read the text content of a web page, scrape articles, or extract information from URLs. Zero dependencies — Python 3 stdlib only. Cross-platform (Mac, Windows, Linux).
When the user wants to solve VRP with Backhauls (VRPB), optimize routes with both deliveries and pickups, or handle reverse logistics. Also use when the user mentions "VRPB," "backhaul optimization," "linehaul and backhaul," "delivery and pickup routes," "reverse logistics," or "return pickups." Backhauls are pickups that occur AFTER all deliveries on a route. For paired pickup-delivery, see pickup-delivery-problem.
Python data processing with pandas, openpyxl, and lxml. Covers DataFrame operations, Excel I/O, XML parsing, bulk data transformation, and large-file handling. Use when processing tabular data, spreadsheets, or XML in Python. USE WHEN: user mentions "pandas", "DataFrame", "openpyxl", "read_excel", "lxml", "XPath", "CSV processing", "Excel parsing", "bulk data", "large file", "data transformation", "UTF-16", "codecs" DO NOT USE FOR: SQL databases (use sql-expert), NumPy-only math, ML/training
A股市场全量数据服务。编排 A股所有细粒度 skill：实时行情、K线、基础数据、市场机制、指数、技术指标。 当用户提及"A股""沪深""创业板""北京交所"且未明确指定数据维度时触发。
Skills covering Upstash Search quick starts, core concepts, and TypeScript/JavaScript SDK usage. Use when a user asks how to get started, how indexing works, or how to use the TS client.
Primary entry point for building, managing, and orchestrating data pipelines on Google Cloud. Guides users to the appropriate skill for dbt, Dataflow (Apache Beam), Dataform, Spark (Dataproc Serverless), BigQuery Data Transfer Service (DTS) or orchestration pipeline using Cloud Composer. Clarify requirements and resolve ambiguity for creating, updating and running data pipelines.
Neo4j Python Driver v6 — driver lifecycle, execute_query, managed and explicit transactions, async (AsyncGraphDatabase), result handling, data type mapping, error handling, UNWIND batching, connection pool tuning, and causal consistency. Use when writing Python code that connects to Neo4j via GraphDatabase.driver, execute_query, execute_read, execute_write, AsyncGraphDatabase, neo4j.Result, or RoutingControl. Package name is `neo4j` (not neo4j-driver) since v6. Python >=3.10 required. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT cover driver upgrades or breaking changes — use neo4j-migration-skill. Does NOT cover GraphRAG pipelines (neo4j-graphrag package) — use neo4j-graphrag-skill.
[Hyper] Investigate websites with Playwriter plus CDP to choose a crawl strategy, capture API/auth evidence, document findings under `.hypercore/crawler/[site]/`, and generate crawler code only after discovery is grounded.
ClickHouse integration. Manage data, records, and automate workflows. Use when the user wants to interact with ClickHouse data.
Analyze option volatility by combining vol surface data, option pricing with Greeks, and historical price data to assess implied vs realized volatility. Use when pricing options, analyzing volatility surfaces, computing Greeks, assessing vol premiums, or evaluating vol trading strategies.
Create, edit, manage, share, or embed MotherDuck Dives. Use when the work involves Dive authoring, live React + SQL components, MCP get_dive_guide, useSQLQuery, local preview, version history, Dives-as-code, required resources, team sharing, or embedded Dive sessions.
Complete guide for dbt data transformation including models, tests, documentation, incremental builds, macros, packages, and production workflows