Total 54,003 skills, Data Processing has 2767 skills
Showing 12 of 2767 skills
Scraper de Macrotrends: financial statements, ratios, employee count con 15+ años de data histórica. Sin API key.
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
Decision framework for choosing between regex and LLM when parsing structured text — start with regex, add LLM only for low-confidence edge cases.
Ingest, QC, and map reads with reproducible outputs. Use for raw read processing and coverage stats.
Unified risk engine with VaR, stress testing, volatility regimes, and automated controls
Build credit scoring models to predict default probability from borrower characteristics. Use this skill when the user needs to assess creditworthiness, build a credit scorecard, or evaluate lending risk — even if they say 'predict default risk', 'credit scoring', or 'loan approval model'.
Apply Benford's Law to detect anomalies in numerical datasets by analyzing first-digit frequency distributions. Use this skill when the user needs to audit financial data for fraud indicators, validate data integrity, or detect fabricated numbers — even if they say 'data manipulation detection', 'first digit test', or 'accounting fraud screening'.
Nextflow DSL 2 TDD implementation workflow. References nextflow-conventions and agent-conduct.
Create a custom technical indicator using Numba JIT + NumPy. Generates production-grade, O(n) optimized indicator functions with charting and benchmarking.
Write, debug, and explain ShopifyQL queries and Shopify Segment Query Language expressions. Use this skill whenever the user wants to query Shopify analytics data, build customer segments, write ShopifyQL for reports, explore sales/orders/products data via the Shopify Admin API, debug a ShopifyQL error, understand available tables/dimensions/metrics, or translate a business question into a Shopify query. Also triggers for: "ShopifyQL", "Shopify analytics query", "customer segment filter", "Shopify segment", "SHOW FROM sales", "GROUP BY in Shopify", "Shopify report query", or any mention of ShopifyQL tables like `sales`, `sessions`, `orders`.
Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.
Salesforce Data Cloud Retrieve phase. TRIGGER when: user runs Data Cloud SQL, describe, async queries, vector search, search-index workflows, or metadata introspection for Data Cloud objects. DO NOT TRIGGER when: the task is standard CRM SOQL (use sf-soql), segment creation or calculated insight design (use sf-datacloud-segment), or STDM/session tracing/parquet analysis (use sf-ai-agentforce-observability).