Skill UI

This guide provides advanced strategies for developers to significantly reduce Perplexity Sonar API billing costs. It covers key techniques including model routing (selecting the right model by query type), setting maximum output tokens, implementing robust query caching, and utilizing domain filters to minimize per-request charges. Essential for building cost-effective, high-volume AI applications.

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.

This comprehensive runbook provides step-by-step procedures for rapidly responding to Perplexity API outages and service degradations. It covers initial triage (checking models, auth, DNS), handling common errors (401, 429, 500/503), implementing fallbacks, and structured post-incident activities, including evidence collection and postmortem documentation.

This skill provides a comprehensive guide to configuring the Perplexity Sonar API across distinct operational environments (development, staging, and production). It details how to manage environment-specific API keys, enforce tailored rate limits, select appropriate models (e.g., sonar vs. sonar-pro), and implement cost optimization strategies. Use this when migrating or integrating Perplexity search functionality into a multi-tier, production-grade application architecture.

This guide provides advanced architectural patterns to optimize interactions with the Perplexity Sonar API. By implementing smart model routing, query hashing with time-to-live (TTL) caching, streaming responses, and rate-limited parallel processing, developers can significantly reduce latency, improve overall throughput, and manage API costs. Ideal for integrating complex, research-intensive search-augmented applications.

This guide implements comprehensive guardrails for Perplexity Sonar API. It covers crucial aspects like query content moderation, PII sanitization, enforcing user usage quotas, selecting appropriate models based on user tiers, and scoring citation reliability to ensure safe, ethical, and cost-effective AI usage.

This guide outlines the comprehensive reference architecture for building advanced, AI-powered search and research applications, modeled after Perplexity. It covers three core tiers: a searchable service with model routing and caching, a citation pipeline for validation and rendering, and an orchestrator for multi-query research synthesis. Use this when designing complex, production-grade, search-augmented LLM integrations or reviewing advanced system patterns.

This skill provides comprehensive patterns for building highly reliable applications that interact with external Large Language Model (LLM) APIs, such as Perplexity Sonar. It implements critical reliability techniques including Circuit Breakers, Model Fallback, Streaming Timeout handling, and Caching layers. Use this to ensure your application maintains high availability and graceful degradation even when external services experience intermittent failures or variable performance.

This comprehensive guide assists developers in migrating their code and API calls when Perplexity updates its model generations or changes API parameters. It provides a clear map from legacy models (pplx-api) to the current Sonar family (sonar, sonar-pro), covering model name changes, base URL updates, parameter adjustments, and SDK upgrade steps. Use this guide whenever you encounter deprecation warnings or need to ensure compatibility with the latest Perplexity Sonar models.

A specialist skill for writing robust, maintainable, and scalable End-to-End (E2E) tests using Playwright. This guide covers setting up test infrastructure, implementing Page Object Model (POM), using role-based selectors, handling API mocking, and debugging flaky tests. Ideal for integrating quality checks into CI/CD pipelines and performing complex browser automation.

An expert assistant providing deep knowledge and best practices for Prisma ORM. It covers the entire lifecycle of database interaction, including optimal schema design, relation modeling, safe migration workflows, and advanced query optimization techniques (addressing N+1 issues and implementing raw queries) across PostgreSQL, MySQL, and SQLite.

A guide to building robust projections and read models from continuous event streams. This pattern is essential for implementing CQRS read sides, creating materialized views, optimizing query performance, and building complex search indexes in event-sourced architectures. Use it when data needs to be transformed and aggregated from raw events into optimized query structures.