Total 53,711 skills, Data Processing has 2765 skills
Showing 12 of 2765 skills
从智慧芽（PatSnap）数据库查询专利法律状态信息。当用户提到专利法律状态、专利有效性核查、专利状态查询、专利事件历史、简单法律状态、转让、许可、质押、异议、诉讼、复审等法律事件、patent legal status, patent validity, patent events, transfer/license/pledge, PatSnap, patent status lookup时触发此技能。当用户询问专利是否处于有效、无效、审中、过期、授权、撤回或撤销状态，或想通过专利ID或公开号查询法律状态时也应触发。
Research aging biology, cellular senescence, and longevity using ToolUniverse. Covers senescence markers and pathways, age-related disease genetics, telomere biology, senolytic drug discovery, epigenetic aging clocks, and longevity gene analysis. Integrates GWAS data, gene expression (GTEx age effects), pathway databases, drug repurposing, and literature. Use when asked about aging mechanisms, senescence, senolytics, longevity genes, age-related diseases, or epigenetic clocks.
A股指数数据与申万行业分类。上证/深证指数行情、成分股权重、申万行业分类。 当用户询问"上证指数""深证成指""申万行业""成分股权重""指数行情"时触发。
Normalize messy creator campaign metrics from multiple sources into a single clean table with standardized field names ready to merge into your master tracker. This skill should be used when cleaning up influencer metrics, standardizing campaign data from multiple platforms, normalizing creator performance numbers, merging metrics from Instagram and TikTok and YouTube into one sheet, formatting messy analytics exports, preparing campaign data for a master spreadsheet, converting raw platform stats into a consistent format, combining metrics from different reporting tools, deduplicating creator data from multiple sources, fixing inconsistent column names across exports, or cleaning up a metrics dump before reporting. For calculating engagement rates, see engagement-rate-calculator-benchmarker. For full campaign reports, see campaign-roi-calculator. For parsing a single Story screenshot, see story-metrics-screenshot-parser.
What DeFi positions does a wallet hold? Protocol-by-protocol breakdown of assets, debts, and rewards across chains.
Databricks integration. Manage Workspaces. Use when the user wants to interact with Databricks data.
Apply event study methodology to measure abnormal returns and cumulative abnormal returns (CAR) around corporate or market events. Use this skill when the user needs to quantify the market impact of announcements, design event and estimation windows, or when they ask 'did this event affect stock price', 'how do I calculate abnormal returns', or 'what is the market reaction to this announcement'.
Guide for Using RQData Data API. Used when you need to query RQData data interfaces and obtain financial data. Supports data queries for markets such as A-shares, Hong Kong stocks, futures, options, indices, funds, and convertible bonds, including HTTP API and Python API documentation.
This skill should be used when the user asks for 'TRX price', 'TRON token price', 'price chart on TRON', 'K-line data for USDT/TRX', 'TRON trade history', 'TRON whale activity', 'large transfers on TRON', 'smart money on TRON', 'TRON DEX volume', or mentions checking real-time prices, candlestick data, trading volume, whale monitoring, or smart money signals on the TRON network. For token search and metadata, use tron-token. For swap execution, use tron-swap.
Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.
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.
通过ASIN获取亚马逊商品详细信息，包括标题、图片、五点描述、规格参数、A+页面、价格、评分评论、变体等。当用户提到亚马逊商品详情、ASIN查询、商品页面数据、Listing分析、五点描述提取、商品图片获取、变体查看、竞品Listing研究、价格查询、评论拆解、商品规格查询、Amazon product details, ASIN lookup, listing analysis, bullet points, variant info, product pricing, ratings and reviews, A+ content, product specifications, product images时触发此技能。即使用户未明确说"商品详情"，只要其需求涉及通过ASIN获取亚马逊商品页面的结构化数据，也应触发此技能。