Skill UI

This setup provides a dedicated local development workflow for integrating with the AppFolio property management API. It allows developers to build and test complex integrations using sophisticated mock endpoints for rapid iteration, eliminating the need to consume live API quotas. Users can toggle between mock mode for swift iteration and sandbox mode for rigorous validation against the actual AppFolio Stack API, ensuring reliable and efficient development.

This guide provides comprehensive strategies to optimize API interactions with the AppFolio property management platform. It covers implementing effective caching strategies, utilizing batch operations for bulk updates, setting up connection pooling, and robust rate limit management. Adopting these techniques significantly reduces API call volume and improves data retrieval performance for large-scale real estate portfolios.

A robust reference architecture designed for integrating multi-property portfolios with the AppFolio Stack API. It manages complex tasks such as real-time vacancy tracking, tenant lifecycle management, work order routing, and financial accounting reconciliation (e.g., QuickBooks/Xero). Key components include a service layer, multi-level caching strategies for optimal data freshness, and an event-driven pipeline (using webhooks and message queues) to ensure data consistency and idempotency across all transactions, addressing potential rate limits and failure modes.

This SDK provides production-ready TypeScript patterns for integrating with the AppFolio property management REST API. It includes a singleton client for centralized credential management, robust error wrappers (handling 429 rate limits and 401 auth errors), a flexible query builder for filtering data, and structured interfaces for core entities like Properties, Tenants, and Leases. Use it to build reliable, scalable automation workflows for real estate operations.

This skill provides robust mechanisms to handle real-time webhook events from the AppFolio property management platform. It processes critical lifecycle events such as tenant onboarding, lease signings, rent payments, and maintenance work order updates. By utilizing these webhooks, developers can securely and instantly sync AppFolio data with external systems (e.g., CRM, accounting, custom dashboards), avoiding inefficient API polling and ensuring data consistency.

Implements automated policy enforcement and guardrails for Canva Connect API integrations. This system enforces best practices such as preventing hardcoded credentials, ensuring proper rate limit handling (429 responses), and validating robust OAuth configurations. It is essential for maintaining high code quality and security in CI/CD pipelines and pre-commit hooks.

A comprehensive guide to implementing secure, scalable, and audited access control for Anthropic enterprise deployments. It details best practices for establishing Organization structures, isolating environments (Dev/Staging/Prod), managing API keys, and implementing Role-Based Access Control (RBAC) to prevent security breaches and control costs.

This comprehensive guide teaches developers how to interact with Claude AI using the official Anthropic SDK. It provides step-by-step instructions on basic message creation, implementing system prompts, and managing multi-turn conversation flows via the Messages API. Ideal for setting up a new Claude integration or testing core API functionality.

A comprehensive runbook designed to guide developers through responding to Anthropic API incidents, including outages, sustained errors (like 529), and rate limit issues. It covers systematic steps like checking the official status page, classifying incident severity, implementing model fallback logic (e.g., downgrading Opus to Sonnet), and conducting post-incident impact assessments to ensure service resilience.

A comprehensive guide detailing 10 common mistakes and best practices when integrating with the Anthropic API (Claude). It covers critical technical aspects such as correctly setting `max_tokens`, using the top-level `system` parameter, managing message alternation, checking `stop_reason`, and optimizing client initialization for robust AI application development.

This guide sets up a fast, cost-effective local development loop for building applications powered by the Anthropic API (Claude). It includes instructions for hot reloading, cost-saving tips (e.g., using Haiku, token limits), and mock client implementation for robust unit testing. It supports both TypeScript/Node.js and Python environments, streamlining the AI development workflow.

Provides best practices for configuring Large Language Model (LLM) access, specifically for Anthropic Claude, across development, staging, and production environments. This guide details setting up separate API keys, selecting appropriate models (e.g., Haiku, Sonnet, Opus), and managing unique rate limits for robust, scalable, and secure LLM integration in enterprise systems.