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Found 46 Skills
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.
Interactive tutorial that teaches Snowflake Dynamic Tables hands-on. The agent guides users step-by-step through building data pipelines with automatic refresh, incremental processing, and CDC patterns. Use when the user wants to learn dynamic tables, build a DT pipeline, or understand DT vs streams/tasks/materialized views.
Design and generate Snowflake Procedures, Java UDTFs, and Task orchestration using AVA placeholders and shard-based parallel execution (00..99).
Interactive tutorial teaching Snowflake Cortex CLASSIFY_TEXT for categorizing unstructured text. Guide users through classifying customer reviews using Python and SQL. Use when user wants to learn text classification, Cortex LLM functions, or analyze unstructured feedback data.
Choose and configure the data warehouse engine connection for CARTO (BigQuery, Snowflake, Redshift, Postgres, Databricks, Oracle).
Apache Iceberg tables on Databricks — Managed Iceberg tables, External Iceberg Reads (fka Uniform), Compatibility Mode, Iceberg REST Catalog (IRC), Iceberg v3, Snowflake interop, PyIceberg, OSS Spark, external engine access and credential vending. Use when creating Iceberg tables, enabling External Iceberg Reads (uniform) on Delta tables (including Streaming Tables and Materialized Views via compatibility mode), configuring external engines to read Databricks tables via Unity Catalog IRC, integrating with Snowflake catalog to read Foreign Iceberg tables
Claude Code skills for analytics and data engineers working with dbt, Snowflake, and data pipelines
Expert-level Snowflake data warehouse platform, virtual warehouses, data sharing, streams, tasks, and SQL optimization
Inside Airbnb data warehouse built with Snowflake and dbt, demonstrating modern analytics engineering patterns with staging, intermediate, and mart layers.
Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to Google Cloud BigQuery. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.
This skill should be used when the user needs a "unique ID generator", "distributed IDs", a "Snowflake ID", asks "UUID vs auto-increment", wants a "time-sortable ID", a "monotonic sequence", a "ticket server", or "ID generation at scale". It gives a menu of ID schemes (UUID/ULID, Snowflake-style, DB ticket/range) with their causality, ordering, and clock-skew trade-offs. Use it whenever a design needs collision-free identifiers across many nodes, even if the user doesn't say "sequencer".
Vercel Connect expert guidance — securely obtain scoped OAuth tokens for third-party services (Slack, GitHub, MCP servers, OAuth, Snowflake) on behalf of apps or users via Vercel OIDC. Use when wiring up third-party API access, connecting to MCP servers, sending Slack messages, accessing GitHub APIs, receiving webhook events from Slack/Linear/GitHub and forwarding them to your agents and apps, or building Eve agent connections.