Skill UI

This comprehensive guide details the ten most common mistakes and anti-patterns encountered when integrating with the Figma REST and Plugin APIs. It covers critical topics such as preventing oversized data fetches, managing rate limits, securing tokens, handling color format conversions, and optimizing data sync using webhooks instead of polling. Essential for code reviews and onboarding. Use when reviewing Figma code, onboarding new developers, or auditing an existing Figma integration.

This guide provides essential best practices for building resilient applications that interact with rate-limited APIs, specifically addressing the CAST AI REST API. It details the implementation of exponential backoff with jitter and utilizing request queuing mechanisms (like p-queue) to gracefully handle HTTP 429 errors. Use this pattern to optimize API call patterns and ensure system stability when making batch or frequent requests.

This guide provides a deep dive into migrating from the deprecated Grammarly Text Editor SDK to the current, server-side REST APIs. It details the architectural shift from client-side embedding to modern API calls, covering how to implement Writing Score (v2), AI Detection (v1), and Plagiarism Detection (v1) using secure token authentication.

This skill implements resilient API interaction patterns for external services. It uses adaptive rate-limiting techniques, including exponential backoff and jitter, to gracefully handle HTTP 429 errors, adapting to undocumented server limits. Furthermore, it provides a dedicated request queue mechanism to manage concurrency, ensuring reliable execution of large-scale, bulk data operations without triggering service throttling.

This skill provides implementation patterns for integrating with the Podium API, a robust platform for business messaging, review management, and payment processing. It demonstrates best practices for using REST APIs with OAuth2 authentication. Users can use this guide to connect their systems, handle complex operations like fetching location data, and implement critical error handling and retry logic for stability.

Qdrant is a high-performance vector database. This client SDK suite provides official, easy-to-use libraries for multiple programming languages (including Python, Java, Go, and TypeScript). It enables developers to seamlessly integrate sophisticated vector search capabilities into their applications, supporting both REST and gRPC APIs. Ideal for building semantic search engines, recommendation systems, and advanced AI applications.

A comprehensive guide for the Veeva Vault local development loop. It details how to interact with the platform using REST APIs, advanced VQL queries for data retrieval, and the VAPIL Java SDK. Ideal for developers implementing solutions involving document management, clinical operations, and CRM processes within the Veeva ecosystem.

This guide provides comprehensive reference architecture for integrating with Veeva Vault, covering REST APIs, VQL query language, and VAPIL Java SDK. It details key concepts like authentication, common data patterns, and error handling, making it essential for developers working on life sciences or CRM solutions built on the Vault platform.

This guide provides the reference architecture and best practices for integrating Wispr Flow's voice-to-text API. It details how to utilize both WebSocket (for low-latency streaming) and REST APIs, covering essential concepts like audio format requirements, context awareness (especially for programming code), and comprehensive error handling strategies.

A comprehensive playbook for API reconnaissance and documentation review. Use this skill early in the testing process to enumerate all reachable endpoints, extract schemas, identify hidden versions (e.g., v1, v2, mobile), and discover undocumented parameters or fields across REST, GraphQL, and mobile APIs. Essential for mapping the full attack surface before deeper exploitation.

A comprehensive playbook for advanced API security testing targeting GraphQL and REST APIs. It guides users through schema introspection, discovering hidden or undocumented fields, analyzing batching capabilities, and identifying authorization gaps (like IDORs). Essential for deep reconnaissance and identifying privilege escalation vectors.

This skill enables developers to integrate X (Twitter) data extraction into applications and AI workflows. It supports SDKs, REST APIs, Apify Actors, and MCP tools for searching tweets, exporting followers, and automating account actions with secure webhooks.