Skill UI

This skill implements robust data privacy controls for interactions with OpenRouter APIs. It automatically detects and redacts Personally Identifiable Information (PII)—such as emails, SSNs, credit cards, and API keys—from prompts. It ensures compliance with privacy regulations like GDPR and CCPA, allowing developers to safely process sensitive data when using various upstream LLM providers.

This bundle provides a structured mechanism for capturing comprehensive debug information when interacting with the OpenRouter API. It captures the full request parameters, response content, detailed error logs, generation metadata (such as cost, token usage, and provider), and the execution environment. This tool is essential for diagnosing failed API calls, unexpected behaviors, or performance/latency issues.

This skill provides comprehensive governance for multi-user API deployments using OpenRouter. It covers key provisioning, including creating, listing, and revoking individual user keys. Users can set per-user budget limits and track usage costs programmatically. It is designed for corporate or team environments that require strict cost control, usage attribution, and detailed usage reporting.

Guides the user through configuring and tuning database connection pools across languages, from selecting pool sizes to setting timeouts and monitoring usage to boost application performance.

This guide details how to implement Role-Based Access Control (RBAC) for Perplexity API in enterprise environments. Since Perplexity lacks native RBAC, the solution involves building a middleware gateway. This gateway enforces granular policies, including team-specific API key usage, model restriction (e.g., limiting access to 'sonar' only), budget caps, rate limiting, and mandatory search domain filtering for compliance and security.

Orchestrate PhantomBuster cloud agents through the Composio MCP integration, automating lead generation, web scraping, usage monitoring, container tracking, CSV exports, and hCaptcha solving in a single workflow.

Profiles application performance by analyzing CPU usage, memory allocation, and execution time with the application-profiler plugin, then identifies bottlenecks and suggests code-level optimizations for faster execution.

A comprehensive guide for profiling, analyzing, and optimizing Python code. It addresses identifying performance bottlenecks related to CPU usage, excessive memory consumption, I/O operations, and slow data processing. Use this skill to improve application speed and efficiency in production environments.

This skill provides comprehensive guardrails for securing Replit-hosted applications. It covers critical security policies including preventing hardcoded secrets, implementing resource usage limits (CPU/Memory), enforcing endpoint authentication, and ensuring proper deployment configuration. Use this when you need to harden a Replit app for production or audit its security posture.

This guide teaches developers how to implement robust rate limiting and handle resource quotas for applications hosted on Replit. It covers monitoring Key-Value database usage, implementing middleware for API rate limiting (using Express), and utilizing exponential backoff and request queuing patterns to ensure application stability and prevent service degradation when hitting resource limits (e.g., 429 errors).

This skill provides comprehensive patterns for data handling and integration with Retell AI. It is designed for developers building advanced voice agents, automating phone calls, or working with complex telephony systems. The guide covers SDK usage, agent listing, and robust error handling, ensuring reliable implementation of voice AI applications.

This skill provides implementation patterns for setting up and managing a multi-environment connection with Retell AI. It is essential for developers building advanced AI voice agents, integrating complex phone call automation, or utilizing robust telephony workflows. It guides users through SDK usage and handles common API error scenarios.