Skill UI

A comprehensive guide to implementing secure integration practices for Linktree APIs. Covers critical topics including secure secret management, robust webhook signature verification (HMAC-SHA256), input sanitization against XSS, and data redaction of Personally Identifiable Information (PII). Essential for developing resilient and secure third-party integrations.

This skill provides the comprehensive workflow for interacting with the Anthropic Messages API. It covers advanced features including streaming responses, multimodal vision input, generating structured JSON output using system prompts, and managing multi-turn conversations. It redirects users to the current, primary guide for all Claude API patterns.

This guide details how to implement robust content safety guardrails for applications powered by Claude. It covers essential techniques such as system prompt hardening, input validation to detect injection patterns and length limits, and output validation to prevent system prompt leakage. It ensures compliance with Anthropic's policies, making the AI integration secure and reliable.

A comprehensive guide to securing Web3 applications utilizing Alchemy. It covers critical best practices, including implementing secure API key proxies, managing private keys via secret vaults, validating blockchain inputs (addresses, block numbers), and verifying webhook signatures to harden your dApp infrastructure.

This module provides comprehensive observability for Anthropic's Claude API integrations. It enables the tracking of critical operational metrics including latency, token usage (input/output), estimated API costs, and error rates. Use it to set up structured logging and Prometheus metrics for robust monitoring and alerting, ensuring reliable and cost-effective AI application deployments.

This comprehensive skill provides multi-layered guardrails for integrating with LLMs like Claude. It enforces security and compliance by implementing input validation (PII detection, length checks), system prompt restriction (scope control, safety rules), output filtering (preventing sensitive data leakage), cost governance, and model access policies. Ideal for building secure, robust, and governed AI applications.

Implements robust rate limiting, backoff logic, and quota management for the Anthropic Claude API. It handles 429 errors and optimizes request throughput by managing Requests Per Minute (RPM), Input Tokens Per Minute (ITPM), and Output Tokens Per Minute (OTPM). This skill provides advanced strategies including SDK retries, custom header awareness, queue-based throttling, and batch processing for stable, high-throughput production applications.

This workflow provides a complete, end-to-end solution for building and deploying robust web scrapers using Crawlee on the Apify platform. It guides users through every stage: defining input schemas, setting up the Actor with a sophisticated router pattern, extracting structured data (e.g., product details), saving results to datasets, and managing the full lifecycle from local testing to cloud deployment via apify-cli.

A comprehensive provider for integrating Eufy security cameras (supporting local P2P or cloud connectivity). This tool facilitates stable RTSP streaming for live monitoring and efficiently captures event-triggered video clips. It is designed for advanced systems that require continuous video feeds and reliable event-based data input for AI analysis and monitoring solutions.

This guide details essential best practices for securing applications integrated with Anthropic's Claude API. It covers critical security measures including secure API key management (server-side only), robust input validation to prevent cost attacks, defense mechanisms against prompt injection, and implementing per-user rate limiting. Essential reading for maintaining data privacy and system integrity in production environments.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

A comprehensive solution for setting up production-grade observability for Cohere API v2. It integrates Prometheus metrics, OpenTelemetry tracing, and robust alerting mechanisms. This skill tracks critical operational data including per-endpoint latency, token consumption (input/output), error rates, and usage costs, ensuring reliable monitoring for AI-powered applications.