Skill UI

This comprehensive guide outlines the process of migrating analytics data from major platforms like Google Analytics, Mixpanel, Amplitude, or Segment to PostHog. It covers implementing a dual-write strategy, mapping historical event names and properties, and performing bulk historical data imports, ensuring a smooth transition and data continuity.

Offers MATLAB and GNU Octave guidance for matrix math, data import/export, visualizations, statistics, signal processing, differential equations, and general scripting—helpful when writing or translating MATLAB/Octave code and running scripts under either interpreter.

This skill provides comprehensive tools for documenting and managing model performance on Hugging Face. It supports multiple methods for adding structured evaluation data, including extracting tables from README content, importing benchmark scores via APIs (like Artificial Analysis), and executing high-performance custom evaluations using advanced backends such as vLLM or lighteval. It ensures that all metadata is structured and compatible with model leaderboards and industry standards.

This skill provides a comprehensive guide and implementation methods for building a robust synchronization bridge between Odoo (ERP system) and WooCommerce (e-commerce store). It covers the automatic synchronization of products, real-time inventory updates, customer records, and the import/mapping of sales orders, ensuring data consistency across both platforms using their respective REST and external APIs.

Structured pipeline for credit risk pre-loan modeling that loads and formats raw data, filters abnormal periods, trims high-missing/low-IV/high-PSI/high-correlation features, denoises via Null Importance, and exports an Excel cleaning report for review.

A comprehensive expert prompt for evaluating Power BI data models. It guides the assessment of model architecture (Star Schema, relationships), storage optimization (Import, DirectQuery, Dual), data quality, performance scalability, and governance best practices. Use this when reviewing an existing BI model to ensure it is robust, maintainable, and highly performant.

Integrate Benchling registry entities, inventory, ELN entries, workflows, and Data Warehouse using the Python benchling-sdk (1.25.0) and v2 REST API. Automates lab data import, FASTA sequence creation, inventory audits, and event-driven Benchling Apps with API key or OAuth authentication.

Build and operate reproducible genomics workloads on DNAnexus using dx CLI, dxpy SDK, apps/applets, native workflows, dxCompiler, and Nextflow. Supports data transfers, execution monitoring, workflow import, and project automation with secure authentication and compliance controls for regulated data handling.

A comprehensive technical guide for executing major data migrations and re-platforming to Intercom. It covers bulk contact imports, syncing conversation histories, migrating company data, and transferring help center articles from source systems like Zendesk or Freshdesk.

This advanced script offers a comprehensive solution for migrating project management data into ClickUp. It facilitates importing structured data from major external tools like Jira, Asana, and Trello, or moving data between disparate ClickUp workspaces. The process handles complex data mapping (e.g., Boards to Spaces, Issues to Tasks), custom fields, and ensures the integrity of hierarchical project structures.

This guide provides a comprehensive strategy for configuring ClickUp API access across development, staging, and production environments. It emphasizes the critical importance of environment isolation using separate API tokens and dedicated workspaces to prevent data leaks and accidental destructive operations in live environments. Includes best practices for secret management (Vault, AWS, GCP) and implementing environment guards.

This skill guides the secure handling and lifecycle management of large-scale data artifacts, including training datasets, model weights, and checkpoint snapshots, within GPU cloud environments. It provides best practices for data pipelines, covering secure import via Kubernetes PVCs, compliant export, and stringent data validation, ensuring adherence to encryption standards (AES-256) and regulatory requirements (PII masking, RBAC).