Skill UI

This comprehensive debug bundle collects all necessary diagnostic evidence from Lucidchart's API integrations. It systematically checks document access, data linking integrity, shape rendering, and export status by capturing API responses, page metadata, and rate limit information. It is essential for support engineers diagnosing complex integration failures without needing direct account access.

This guide provides advanced strategies for optimizing interactions with the Notion API. Learn best practices such as implementing Time-To-Live (TTL) caching, batching multiple block updates, avoiding inefficient N+1 query patterns, and managing rate limits. Use this when your Notion application suffers from slow responses, high latency, or excessive API call consumption.

This skill establishes a local development loop for OneNote integrations. It uses Mock Service Workers (MSW) to intercept calls to the Microsoft Graph API, providing realistic, fixture-based responses (e.g., Notebooks, Sections, Pages). This allows developers to rapidly build and test OneNote features without needing live Azure credentials or worrying about rate limit restrictions during development cycles.

This guide provides advanced techniques for optimizing performance within Palantir Foundry. It covers efficient pagination, implementing client-side caching, using batch object retrieval (solving the N+1 problem), and tuning Spark transforms with memory configuration and incremental updates. Use this when experiencing slow API responses or inefficient data pipeline builds in Foundry.

This skill is designed to collect comprehensive diagnostic information regarding Persona identity verification processes. It retrieves inquiry IDs, current status, API responses, and webhook delivery logs. It is essential for troubleshooting issues related to KYC and identity verification workflows, ensuring smooth API connectivity and data flow.

This guide provides a comprehensive workflow for developing and testing with Persona's identity verification services in a controlled sandbox environment. It details setting up local environment variables, tunneling webhooks using ngrok, creating test inquiries via API, and mocking API responses for robust unit and integration testing.

A comprehensive TypeScript client wrapper for interacting with the Persona API. It simplifies identity verification workflows by providing methods for creating, retrieving, and paginating inquiries and verifications. Key features include implementing the Singleton design pattern, guaranteeing type-safe responses, and an advanced error classifier that intelligently handles retry logic (e.g., distinguishing between rate limits and invalid keys). Ideal for integrating reliable, production-grade KYC flows into applications.

This skill provides a comprehensive workflow for managing Requests for Information (RFIs) within the Procore platform. It enables users to programmatically create, assign, update responses, track status changes, and officially close RFIs using the Procore API. Ideal for automating critical steps in construction project management.

This skill provides detailed implementation patterns for handling rate limits when connecting to QuickNode's blockchain RPC endpoints and utilizing the QuickNode SDK. It is essential for developers building robust Web3 applications, guiding them through connection setup, best practices, and resolving common blockchain errors such as 401 Unauthorized or Rate limited responses.

This comprehensive guide details setting up robust CI/CD pipelines using GitHub Actions for testing SalesLoft API integrations. It enables running unit tests with mocked responses, performing live integration tests against the actual SalesLoft API (including OAuth token validation and connectivity checks), and ensuring deployment stability. Use this skill when automating quality assurance, validating API endpoints, or managing complex SaaS workflow deployments.

This utility provides a robust local development loop for integrating search APIs (like SerpApi). By caching real search responses into fixtures, developers can test search integrations, write unit tests, and develop features offline without incurring continuous API costs. It includes detailed instructions and code examples for Python and Node.js, ensuring cost-effective and reproducible testing.

This guide provides a comprehensive tutorial on running various AI inference tasks using the Together AI API, which is compatible with the OpenAI standard. It demonstrates key functionalities including chat completions, streaming responses, image generation, and creating embeddings. This is ideal for developers who need to test open-source models, compare performance across different LLMs (like Llama or Mixtral), or integrate powerful generative AI features into their applications using Python or Node.js.