Skill UI

A comprehensive diagnostic tool designed for deep debugging of complex Exa system issues. It systematically checks multiple layers (DNS, Authentication, Neural Search, Content Retrieval, etc.) and provides detailed latency profiling (p50, p95) to pinpoint performance bottlenecks or intermittent failures. Use this when standard troubleshooting steps fail or when preparing detailed evidence for support escalation.

A comprehensive guide to diagnosing and resolving common errors and status codes (400, 401, 429, etc.) encountered when integrating with the Exa API. Provides specific solutions for malformed requests, authentication failures, rate limit issues, and content fetching errors, ensuring smooth API debugging and integration.

This guide provides comprehensive instructions for developers to install and set up the Exa SDK (exa-js for Node.js, exa-py for Python). It covers setting up API key authentication using environment variables and demonstrates client initialization for both major languages, enabling developers to utilize Exa's neural search API for web content retrieval.

This guide provides a comprehensive pattern for creating robust and scalable FastAPI routers. It covers essential best practices, including implementing proper authentication logic (required/optional dependencies), defining structured response models using Pydantic, and correctly assigning HTTP status codes. Use this skill when building structured and secure Python backend APIs.

Automates guidance for API filtering query builder tasks, offering industry best practices, production-ready code, and validation across REST, GraphQL, OpenAPI, and authentication design patterns.

Performs a structured, multi-phase audit on local branch changes (diffs) to identify security vulnerabilities, bugs, and code quality issues. It systematically checks for common risks like Injection (SQL, XSS), Broken Authentication, IDOR, CSRF, and business logic flaws, providing detailed severity, evidence, and suggested fixes. Ideal for pre-merge code reviews and security audits.

This comprehensive skill covers the full scope of Firebase services, including Authentication, Firestore, Cloud Functions, and Hosting. It goes beyond basic implementation, focusing on critical architectural principles: adopting a query-first, denormalized NoSQL mindset. Key insights include mandatory security rule design, optimal data modeling for performance, and correctly utilizing modular SDKs to build scalable and secure backends.

Scans Android APKs for Firebase misconfigurations, testing databases, storage, authentication, and cloud functions to surface vulnerabilities during mobile security audits.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

A comprehensive checklist for securely deploying and validating applications using Firecrawl's core APIs (scrape, crawl, map, extract) in a production environment. It covers critical areas including secure credential management, implementing crawl safety limits, robust error handling (rate limits, authentication failures), establishing monitoring alerts, and executing necessary rollback procedures.

This comprehensive guide serves as a quick reference for diagnosing and fixing common errors encountered when interacting with the Fireflies.ai GraphQL API. It covers specific error codes (e.g., authentication failure, rate limits, invalid parameters) and provides actionable fixes, diagnostic scripts, and schema introspection techniques, ensuring seamless API integration and rapid troubleshooting.

This guide details the comprehensive setup process for authenticating with the Fireflies.ai GraphQL API. It covers retrieving the API key, configuring environment variables, and verifying connectivity using code examples for Node.js, Python, and cURL. Essential for securely integrating Fireflies data into external applications and automating transcript access.