Skill UI

A comprehensive workflow for setting up CI/CD pipelines for Flexport logistics integrations. This tool automates unit testing with mocked data, and executes live API contract validation against the Flexport sandbox upon merging to the main branch. It ensures data transforms and API compatibility across shipment lifecycle events, covering core logistics functions like booking, tracking, and customs documentation.

This skill provides instructions for deploying Flexport logistics integrations across various cloud platforms, including Vercel, Fly.io, and Google Cloud Run. It is essential for setting up reliable, always-on webhook receivers, shipment tracking dashboards, and background workers necessary for comprehensive supply chain automation services in a production environment.

Implements robust webhook event handling for Flexport, enabling real-time tracking and processing of critical logistics updates. It manages shipment milestones (e.g., departed, arrived, delivered), booking confirmations, PO changes, and invoice events. Includes signature verification (HMAC-SHA256) and idempotent processing to ensure reliable supply chain data integration.

This guide provides a systematic approach to deep debugging complex HubSpot API issues. It includes layer-by-layer network testing (DNS, TCP, TLS), correlation ID tracking, and timing analysis to isolate intermittent or hard-to-reproduce errors. Use this when standard troubleshooting fails or when compiling detailed evidence for technical support.

This script provides a minimal, working example using the Node.js SDK to interact with the Klaviyo API. It demonstrates core capabilities: creating or updating user profiles, tracking custom events associated with those profiles, and querying profile data. This is ideal for initial integration setup, testing basic API connectivity, or learning the foundational patterns of profile management and event tracking in an e-commerce marketing context.

A comprehensive guide to implementing observability for Klaviyo API integrations. This solution uses Prometheus metrics (counters, histograms, gauges) to track API volume, latency, and errors, combined with OpenTelemetry for distributed tracing and structured logging. Ideal for setting up robust monitoring dashboards and critical alerting systems for marketing data pipelines.

A logging wrapper designed to instrument and monitor calls to the Claude API. It automatically tracks critical metrics including token usage, API latency, estimated cost, and error details. Essential for implementing robust observability patterns and setting up proactive alerts in production environments.

A comprehensive guide and implementation pattern for handling rate limits and quotas across various Adobe APIs (Firefly, PDF Services, Photoshop, etc.). This includes implementing exponential backoff, honoring `Retry-After` headers, and proactive quota tracking to ensure stable, high-throughput batch operations and reliable integration.

A comprehensive guide to implementing advanced user behavior tracking and real-time data synchronization with Algolia. This guide demonstrates how to use the Insights API to track clicks, conversions, and views, and how to build event-driven pipelines using database change listeners (e.g., Prisma middleware) to keep your Algolia index perfectly synced with your core application data. Essential for deep search analytics and relevance tuning.

This specialized skill provides a robust framework for tracking and updating financial investment signals. It systematically assesses the impact of new market information—such as breaking news or price movements—on existing investment theses. The system determines if a signal is Strengthened, Weakened, Falsified, or Unchanged, providing a crucial layer of continuous signal validation for sophisticated financial decision-making.

A suite of utilities designed to significantly boost Anima code generation performance. It implements file-based caching with Time-To-Live (TTL) management, enables incremental updates by tracking only changed Figma components, and optimizes output size by cleaning up comments and excess whitespace. Ideal for optimizing large batch generations or speeding up production build pipelines.

This skill provides a comprehensive guide to optimizing costs when using AssemblyAI for speech-to-text transcription. It details model selection (Best vs. Nano), guides feature budgeting (e.g., Diarization, Sentiment Analysis), and includes code examples for cost estimation and usage tracking. Use this when managing billing, reducing operational expenses, or implementing budget alerts for high-volume audio processing.