Total 30,538 skills, Data Processing has 1462 skills
Showing 12 of 1462 skills
Optimizes Snowflake query performance using query ID from history. Use when optimizing Snowflake queries for: (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing query performance metrics - bytes scanned, spillage, partition pruning (4) User references a previously run query that needs optimization Fetches query profile, identifies bottlenecks, returns optimized SQL with expected improvements.
Develops and troubleshoots dbt incremental models. Use when working with incremental materialization for: (1) Creating new incremental models (choosing strategy, unique_key, partition) (2) Task mentions "incremental", "append", "merge", "upsert", or "late arriving data" (3) Troubleshooting incremental failures (merge errors, partition pruning, schema drift) (4) Optimizing incremental performance or deciding table vs incremental Guides through strategy selection, handles common incremental gotchas.
Converts legacy SQL to modular dbt models. Use when migrating SQL to dbt for: (1) Converting stored procedures, views, or raw SQL files to dbt models (2) Task mentions "migrate", "convert", "legacy SQL", "transform to dbt", or "modernize" (3) Breaking monolithic queries into modular layers (discovers project conventions first) (4) Porting existing data pipelines or ETL to dbt patterns Checks for existing models/sources, builds and validates layer by layer.
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
Finds and ranks expensive Snowflake queries by cost, time, or data scanned. Use when: (1) User asks to find slow, expensive, or problematic queries (2) Task mentions "query history", "top queries", "most expensive", or "slowest queries" (3) Analyzing warehouse costs or identifying optimization candidates (4) Finding queries that scan the most data or have the most spillage Returns ranked list of queries with metrics and optimization recommendations.
Enrich contact and company data using x402-protected APIs. Superior to generic web search for structured business data. USE FOR: - Enriching person profiles by email, LinkedIn URL, or name - Enriching companies by domain - Finding contact details (email, phone) with confidence scores - Scraping full LinkedIn profiles (experience, education, skills) - Searching for people or companies by criteria - Bulk enrichment operations (up to 10 at a time) TRIGGERS: - "enrich", "lookup", "find info about", "research" - "who is [person]", "company profile for", "tell me about" - "find contact for", "get LinkedIn for", "get email for" - "employee at", "works at", "company details" ALWAYS use x402.fetch for enrichx402.com endpoints - never curl or WebFetch. Returns structured JSON data, not web page HTML. IMPORTANT: Never guess endpoint paths. All paths follow the pattern https://enrichx402.com/api/{provider}/{action}. Use exact URLs from the Quick Reference table below or call x402.discover_api_endpoints first.
Best practices for creating comprehensive Jupyter notebook data analyses with statistical rigor, outlier handling, and publication-quality visualizations
Expert in Galaxy workflow development, testing, and IWC best practices. Create, validate, and optimize .ga workflows following Intergalactic Workflow Commission standards.
Extract and analyze business descriptions and competitive landscape from SEC filings using Octagon MCP. Use when researching company business models, market positioning, competitive advantages, industry dynamics, and strategic focus areas from Item 1 disclosures.
Retrieve detailed revenue breakdown by product segment for public companies. Use when analyzing product mix, revenue concentration, segment contribution, or business line performance.
Retrieve analysts' price target summary for any stock using Octagon MCP. Use when evaluating analyst sentiment, upside/downside potential, consensus expectations, and tracking target trends over time.
Extract management's commentary on specific topics from earnings call transcripts, including product development, strategy, competitive positioning, and executive quotes.