Skill UI

This SDK enables developers to build robust document analysis applications using Azure AI Document Intelligence. It provides powerful capabilities to extract structured data from diverse document types, including receipts, invoices, ID cards, and general forms. Developers can analyze documents from local files or URLs to extract key-value pairs, tables, and specific fields automatically.

This SDK enables developers to build robust document analysis applications using Azure AI Document Intelligence. It provides powerful capabilities to extract structured data from diverse document types, including receipts, invoices, ID cards, and general forms. Developers can analyze documents from local files or URLs to extract key-value pairs, tables, and specific fields automatically.

A comprehensive guide and code implementation for scaling data enrichment pipelines to handle high volumes (10K-100K+ leads monthly). It covers capacity planning, optimizing batch processing using queues (e.g., BullMQ/Redis), managing rate limits, and designing multi-table architectures for robust, large-scale data ingestion.

A comprehensive utility designed to collect all necessary diagnostic evidence for troubleshooting Ideogram API interactions. It gathers environment details (Node, Python, OS), performs API connectivity tests, captures network information, and packages the results into a redacted tarball suitable for attaching to technical support tickets, ensuring all sensitive data is masked.

Visits target URLs to capture screenshots and inspect pages, then extracts palettes, typography, layouts, and repeatable UI patterns so design teams can document inspiration for new projects.

A production-ready Python SDK providing comprehensive patterns for integrating with the Kling AI API. This wrapper handles crucial operational complexities such as auto-refreshing JWT tokens, structured request/response models, exponential backoff polling for long-running tasks, and detailed error handling. Use this library when building stable, high-reliability applications that require advanced text-to-video or image-to-video synthesis capabilities.

Implement robust, structured logging for API requests, capturing performance metrics, correlation IDs, and detailed security audit trails. This skill ensures compliance by handling PII redaction and providing comprehensive, JSON-formatted logs suitable for ELK Stack or Loki. Essential for debugging, performance analysis, and maintaining SOC 2 compliance in distributed microservices.

A comprehensive guide and implementation for setting up a fast, cost-effective local development loop for the Perplexity Sonar API. It includes generating type-safe client wrappers, utilizing fixtures for reliable mocking, and establishing a complete test suite with hot-reloading capabilities. This ensures stable development and manages high API call costs during iteration.

A comprehensive runbook for managing and resolving common incidents within the TwinMind meeting AI platform. This guide covers failures such as transcription not starting, audio capture issues, syncing errors, and calendar disconnections. It provides API setup, code snippets, and detailed troubleshooting steps to ensure a stable, continuous meeting AI workflow.

A comprehensive toolkit for automating and testing local web applications using Python and Playwright. It supports complex dynamic interactions, managing server lifecycles, identifying stable selectors, capturing visual evidence (screenshots), and debugging UI behavior. The guides follow a robust 'Reconnaissance-Then-Action' pattern for reliable end-to-end testing.

This skill simulates security incidents using discussion-based tabletop exercises for Security Operations Center (SOC) teams. It is designed to test incident response procedures, evaluate cross-functional communication workflows (e.g., Legal, PR, Executive), and assess decision-making capabilities under pressure, all without touching production environments. Ideal for compliance validation, playbook refinement, and comprehensive team training.

Models cap table dilution, SAFE conversion, and exit waterfalls for venture rounds, generating OCF inputs and running Python scripts to calculate ownership changes and waterfall outcomes.