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Found 49 Skills
Sets up and operates Airbyte Agent Connectors — strongly typed Python packages for accessing 51+ third-party SaaS APIs through a unified entity-action interface. Supported services include Salesforce, HubSpot, Stripe, GitHub, Slack, Jira, Shopify, Zendesk, Google Ads, Notion, Linear, Intercom, Gong, and 36 more connectors spanning CRM, billing, payments, e-commerce, marketing, analytics, project management, helpdesk, developer tools, HR, and communication platforms. Make sure to use this skill when the user wants to connect to any SaaS API, install an airbyte-agent connector package, integrate third-party service data into a Python application or AI agent, query or search records from any supported service, or configure Airbyte MCP tools for Claude. Covers Platform Mode (Airbyte Cloud) and OSS Mode (local Python SDK).
API de Estadísticas Monetarias v4.0 del BCRA con 638 series macroeconómicas (reservas, tipo de cambio, tasas, M1/M2/M3, inflación, CER, UVA).
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
Detect the divergence phenomenon where commodity prices rise but the holdings of corresponding physical ETFs/trusts decline, and use multi-indicator cross-validation to assess the risk of physical supply tightness/delivery pressure.
Comprehensive guide for NumPy - the fundamental package for scientific computing in Python. Use for array operations, linear algebra, random number generation, Fourier transforms, mathematical functions, and high-performance numerical computing. Foundation for SciPy, pandas, scikit-learn, and all scientific Python.
Converts JSON data snippets into Python Pydantic data models.
Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python
Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.
Find substitute materials using CWICR data. Identify equivalent alternatives based on function, cost, and availability.
Best practices for NumPy array programming, numerical computing, and performance optimization in Python
Create publication-quality matplotlib/seaborn charts with readable axes, tight layout, and curated palettes.
Implement analytics, data analysis, and visualization best practices using Python, Jupyter, and modern data tools.