Total 54,172 skills, Data Processing has 2771 skills
Showing 12 of 2771 skills
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, ....
Split Excel workbooks into separate Excel files by worksheet, with each worksheet generating an individual file. Application scenarios: (1) Split multi-worksheet Excel files into separate files, (2) Extract specific worksheets as independent files, (3) Distribute worksheets from merged workbooks, (4) Create copies of worksheets for separate processing or distribution.
Implement a web crawler pipeline covering URL discovery, fetching, parsing, and storage. Use this skill when the user needs to build a site crawler, audit website structure, or collect web data systematically — even if they say 'scrape a website', 'crawl all pages', or 'site audit spider'.
Build forecasting models with Meta's Prophet for business time series with holidays and changepoints. Use this skill when the user needs user-friendly time series forecasting, handling of missing data and holidays, or automatic changepoint detection — even if they say 'forecast with Prophet', 'business forecast', or 'easy time series model'.
Generates a comprehensive client health overview across all accounts. Reads CRM data, support tickets, usage metrics, billing, and engagement logs. Calculates health scores, trend direction, and RAG status per client. Outputs a sorted risk report with recommended actions.
Use Bitquery GraphQL through UXC for onchain trades, transfers, token holder analysis, balances, and market structure queries across supported networks, with OAuth client_credentials authentication and query-first execution.
Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens
Query real-time market and valuation data such as the latest closing price, opening price, price change percentage, turnover amount, trading volume, turnover rate, PE, PB, and market capitalization for A-shares, H-shares, U.S. stocks, and their indices. Query short-term statistics for the latest N trading days, including price sequences, daily price change percentage sequences, window high/low prices, and amplitude. Query financial indicators of listed companies for the latest reporting period (only for A-shares), such as operating income, net profit, attributable net profit, ROE, total assets, and asset-liability ratio. Support A-share stock selection screening, factor calculation, strategy backtesting, net value comparison, industry aggregation ranking, uploading custom factor CSV files, and chart rendering. Currently, H-shares and U.S. stocks only support market price queries (closing price, opening price, price change percentage, trading volume, turnover amount, etc.). Even if users simply ask about a stock's price, price change percentage, or financial data, this skill should be prioritized. Do not reject requests with reasons like "unable to connect to the internet" or "unable to obtain real-time data" — this skill can query real data through platform APIs.
Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, or semantic nearest-neighbor lookup. Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext/keyword indexes (FULLTEXT INDEX, db.index.fulltext) — use neo4j-cypher-skill. Does NOT handle GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.
Extract structured data from web pages using browser automation and DOM queries
Analyze HLA genes, MHC binding, epitope-MHC associations, and immunogenomics for transplant compatibility, vaccine design, and immunotherapy. Integrates IMGT, IEDB, BVBRC, UniProt, and DGIdb. Use for HLA typing interpretation, antigen presentation analysis, MHC restriction, neoantigen prediction context, and transplant immunology.