Skill UI

A comprehensive guide to optimizing API interactions with BambooHR. Learn advanced techniques like eliminating N+1 queries using custom reports, implementing incremental syncing with 'changed-since' endpoints, robust response caching (LRU/Redis), connection pooling, and request batching. Use this when facing slow API responses or needing high-throughput data synchronization.

This skill provides advanced strategies for optimizing Canva Connect API performance. It covers implementing robust caching mechanisms (in-memory and Redis) to reduce redundant calls, handling pagination using continuation tokens, and implementing smart polling with progressive backoff for asynchronous operations like exports. It also details connection pooling and concurrency management to maximize request throughput and minimize latency for stable Canva integrations.

A comprehensive guide to production-ready patterns for integrating with Anthropic's Claude API using both TypeScript and Python SDKs. Covers robust client setup (retries, timeouts), advanced error handling, streaming implementations, prompt caching, and batch processing to ensure high performance and cost efficiency in real-world AI applications.

This guide provides strategies to minimize API overhead when integrating with Clari. Users can optimize export frequency (e.g., daily vs. quarterly), implement data caching, and restrict data exports to only the necessary types, thereby reducing operational costs and improving system performance.

A persistent memory kit designed for Claude AI agents. It maintains deep context across multiple sessions and projects using a two-layer architecture (hot cache and knowledge wiki). Features include safety hooks, multi-project context isolation, and a /close-day command for daily synthesis, ensuring agents remember complex information and continuously learn.

This comprehensive guide provides advanced strategies for optimizing throughput and reducing latency when interacting with the ClickUp API v2. Key techniques covered include implementing cache hierarchies, efficient asynchronous pagination, connection pooling, and rate limit adherence. Essential for building scalable and reliable automated integrations.

A comprehensive guide for configuring and integrating the Cohere API v2 across development, staging, and production environments. This pattern ensures environment-specific settings—including API keys, model selections, token limits, and caching strategies—are correctly applied. It covers best practices for secure secret management using tools like Vault, AWS Secrets Manager, and GCP Secret Manager, ensuring robust and scalable deployments.

A comprehensive guide for optimizing Cohere API v2 performance. Learn advanced strategies to improve throughput, reduce latency, and manage costs when using Chat, Embed, and Rerank endpoints. Techniques covered include dynamic model selection based on latency budgets, implementing streaming for faster perceived response times, efficient batch processing for embeddings, vector compression, and robust caching mechanisms.

This comprehensive guide provides a production-grade reference architecture for building robust Text-to-Speech (TTS) and voice applications using the ElevenLabs API. It covers detailed project structure, service layer design (including TTS orchestration, voice management, and caching), configuration handling, and best practices for streaming and multi-model orchestration, ensuring scalability and reliability in a commercial SaaS environment.

This guide provides best practices for optimizing Fathom API usage and managing associated cloud costs. It covers strategies like implementing caching for transcripts, switching from API polling to webhooks, batching CRM writes, and establishing data retention policies (e.g., archiving after 90 days) to minimize unnecessary spending on storage and API calls.

This guide provides advanced strategies for optimizing bulk data synchronization and reducing latency when interacting with the Fathom meeting intelligence API. Techniques covered include implementing granular caching strategies (different TTLs for transcripts vs. action items), efficient batch processing with rate limit management, connection pooling, and robust error handling for reliable, high-throughput data operations.

This skill guides the secure configuration of Figma API access across development, staging, and production environments. It details best practices for managing separate API tokens (PATs), file keys, and cache settings. The focus is on implementing robust environment guards and utilizing secret management solutions to prevent cross-environment data leakage and accidental operations.