Skill UI

This skill provides comprehensive management for team access to AI APIs, ensuring security and accountability. It allows setting up role-based access control (admin, editor, viewer), implementing per-member and total team usage quotas, and managing separate API keys across Development, Staging, and Production environments. Ideal for scaling AI usage in enterprise settings.

This module implements comprehensive Role-Based Access Control (RBAC) for multi-tenant LangChain applications. It provides granular permission models for controlling model access, tool execution, and chain invocation. Key features include multi-tenant data isolation in vector stores, enforcing usage quotas (token limits), and integrating middleware for robust security enforcement. Ideal for building secure, scalable, and compliant enterprise LLM systems.

This guide provides advanced techniques for managing API rate limits (429 errors) and complexity budgets when interacting with the Linear API. It covers reading rate limit headers, implementing exponential backoff with jitter for robust retries, controlling request bursts via token buckets, and optimizing GraphQL queries to minimize complexity scores. Use this when developing reliable integrations that must adhere to strict API quotas.

This skill provides a comprehensive framework for implementing robust API rate limiting. It supports advanced algorithms like sliding windows, token buckets, and fixed counters, backed by Redis for distributed state. Use it to protect endpoints from excessive requests, enforce tiered quotas (Free, Pro, Enterprise), and prevent abuse like brute-force attacks by setting per-user, per-endpoint, or per-API-key limits.

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).

A comprehensive guide on optimizing Sentry observability costs. Learn techniques such as SDK-level error sampling, fine-grained performance tracing control, and event filtering using the `beforeSend` hook. These methods significantly reduce the volume of error and transaction data sent, allowing users to manage quotas and prevent overage charges without losing visibility into mission-critical production errors.

This advanced guide provides strategies for scaling Sentry in high-traffic, enterprise-level applications handling millions of events daily. It details implementing adaptive sampling based on endpoint criticality, using adaptive error deduplication to manage quotas, and optimizing the SDK for minimal runtime overhead, ensuring robust visibility even under extreme load.

A comprehensive guide to managing Sentry's event volume, quotas, and rate limits. Learn how to prevent 429 Too Many Requests errors and control costs by implementing client-side sampling (sampleRate/tracesSampleRate), using beforeSend filters to drop noisy errors, and understanding various quota types (Errors, Transactions, Replays). Essential for high-volume, cost-sensitive applications.

A comprehensive guide for managing resource limits and quotas across all Supabase services (API, Auth, Storage, Realtime, Edge Functions). Learn how to understand tier-specific limits, configure connection pooling using Supavisor (Transaction/Session mode), and implement robust retry logic with exponential backoff to gracefully handle 429 rate limiting errors, ensuring high application reliability.

A comprehensive guide and implementation pattern for handling rate limits and quotas across various Adobe APIs (Firefly, PDF Services, Photoshop, etc.). This includes implementing exponential backoff, honoring `Retry-After` headers, and proactive quota tracking to ensure stable, high-throughput batch operations and reliable integration.

This guide demonstrates best practices for implementing robust API rate limiting, backoff strategies, and session throttling patterns. It provides solutions for handling common API quota issues, such as 429 errors, and managing high volumes of concurrent encounters. It is essential for building stable, high-throughput systems in SaaS and healthcare environments.

Implements automated, multi-layered policy enforcement and guardrails for Adobe integrations. This skill provides crucial security checks, including detecting sensitive credentials (e.g., p8_ secrets), pre-screening content for services like Firefly (blocking trademarks or explicit material), and enforcing usage quotas for PDF Services. It is essential for maintaining secure and compliant CI/CD pipelines.