Skill UI

This guide provides essential security best practices for implementing Langfuse, an LLM observability platform. It covers critical areas such as secure credential management (public vs. secret keys), implementing PII scrubbing techniques before tracing, hardening self-hosted environments, and enforcing the principle of least privilege. Use this guide to ensure your LLM integrations meet strict data privacy standards (e.g., GDPR, HIPAA).

This skill provides comprehensive guidance for senior-level Laravel engineering. It focuses on building production-grade, maintainable, and highly secure applications using modern architectural patterns (clean architecture, services, etc.). Use this when developing new features, refactoring complex code, designing robust APIs, or optimizing database interactions within a Laravel environment. Adheres to best practices like Eloquent optimization and proper authentication flows.

A specialized security auditor for Laravel applications. It analyzes code, APIs, and configurations against OWASP standards to detect vulnerabilities such as XSS, IDOR, SQL injection, and misconfigurations. Ideal for reviewing backend logic to ensure robust data protection and authorization.

This skill provides comprehensive patterns for integrating external applications with the Lindy AI platform. It covers three primary channels: Webhook triggers for receiving inbound data, HTTP actions for making outbound API calls, and executing custom Python/JavaScript code (Run Code). Use this when building complex, multi-step automation workflows or connecting internal systems to Lindy agents.

Comprehensive skill for configuring advanced Lindy AI integration using webhooks. This covers three key patterns: Inbound webhooks (external systems triggering Lindy), Outbound requests (Lindy calling external APIs), and two-way Callback mechanisms for asynchronous communication. Use this skill when building complex, event-driven workflows that require reliable, real-time data exchange between your applications and the AI agent.

This skill provides comprehensive patterns for synchronizing, backing up, and maintaining data consistency between a local database and the Linear API. It covers full pagination sync, efficient webhook-based incremental updates, and conflict resolution. Implement this when building client applications that require a reliable, up-to-date local mirror of Linear issue data.

A comprehensive guide to optimizing interactions with the Linear API. Learn advanced techniques to improve application performance by eliminating N+1 queries, implementing robust caching strategies for static data (e.g., teams, states), managing cache invalidation via webhooks, and efficiently batching multiple mutations into single GraphQL requests. Essential for building scalable, low-latency SaaS applications.

Execute comprehensive load, stress, and soak tests to validate API performance, identify scaling bottlenecks, and establish throughput baselines. This tool simulates realistic, high-volume traffic patterns using industry-standard tools like k6 or Artillery, allowing users to define complex scenarios (e.g., e-commerce checkout flows, traffic spikes) and assert performance thresholds (p95 latency, error rates). It helps pinpoint resource limitations in databases, network layers, or compute resources, ensuring the API is ready for production scalability.

A comprehensive deep dive guide for migrating translation memory (TM) and localization content from competing Translation Management Systems (TMS) like Crowdin, Phrase, or POEditor into Lokalise. This process involves exporting data from the source platform, transforming key variables and file structures to match Lokalise conventions, and finally performing a bulk API upload to establish a new, centralized localization repository. Perfect for re-platforming or migrating existing translation pipelines.

This guide provides production-grade coding patterns for integrating Lokalise into TypeScript and Node.js applications. It covers crucial best practices such as client singleton implementation, robust cursor-based pagination for large datasets, structured error handling with retry logic, and efficient batch operations. Implementing these patterns ensures reliable, scalable, and maintainable API usage.

A comprehensive debugging toolkit designed for diagnosing complex issues within MaintainX integrations. It includes environment diagnostics, detailed request/response logging (using interceptors), and robust health checks for multiple core API endpoints. Use this when troubleshooting connectivity, data integrity, or unexpected API behavior.

This guide demonstrates how to implement robust Role-Based Access Control (RBAC) for MaintainX integrations using TypeScript and Express. It defines multiple user roles (Admin, Manager, Technician, Viewer) with specific, granular permissions across various resources (work orders, assets, locations). The implementation utilizes permission middleware and scoped API keys to ensure that users can only perform actions designated by their assigned role, enforcing security and data integrity at the API level.