Total 50,487 skills, Data Processing has 2559 skills
Showing 12 of 2559 skills
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.
Build reliable data pipelines and analytics-ready datasets. USE when cleaning data, designing ETL/ELT, defining contracts, or shipping reproducible data workflows.
Extract structured data from web pages using browser automation and DOM queries
Track workouts, stats, progress over time. Identify improvement areas, plateaus, rest/recovery needs, peak performance timing, injury risk.
Run Neo4j Graph Analytics algorithms (PageRank, Louvain, WCC, Dijkstra, KNN, Node2Vec, FastRP, GraphSAGE) directly inside Snowflake without moving data. Use when running graph algorithms against Snowflake tables via the Neo4j Snowflake Native App ("GDS Snowflake", "graph algorithms in Snowflake", "Neo4j Graph Analytics"). Covers installation, privilege setup, project-compute-write pattern, and SQL CALL syntax. Does NOT cover Cypher or Neo4j DBMS queries — use neo4j-cypher-skill. Does NOT cover Aura Graph Analytics — use neo4j-aura-graph-analytics-skill. Does NOT cover self-managed GDS — use neo4j-gds-skill.
Use when working with DataAsset, DataTable, soft reference, hard reference, TSoftObjectPtr, async loading, Asset Manager, StreamableManager, or game data structures in Unreal Engine. See references/asset-loading-patterns.md for async loading and StreamableManager patterns. See references/data-driven-design.md for data-driven gameplay architecture. For serialization, see ue-serialization-savegames. For C++ foundations, see ue-cpp-foundations.
通过Eureka专利数据平台获取翻译后的专利说明书（描述）文本。当用户要求专利说明书翻译、其他语言的专利全文、翻译后的专利全文，或想查看中文、英文、日文版的专利说明书、Eureka专利说明书、patent specification translation, patent description translation, Eureka patent, patent translation时触发此技能。当用户提供专利ID或公开号并要求获取其他语言的说明书/描述内容，或提到"专利说明书翻译"、"描述翻译"、"翻译全文"等类似意图时也应触发。
Foundational plotting library. Create line plots, scatter, bar, histograms, heatmaps, 3D, subplots, export PNG/PDF/SVG, for scientific visualization and publication figures.
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython (Bio.Entrez). Use this for direct HTTP/REST work or custom API implementations.
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.
Query ChEMBL's bioactive molecules and drug discovery data. Search compounds by structure/properties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.