Skill UI

This skill provides a comprehensive operational checklist for identifying and exploiting HTTP Parameter Pollution (HPP) vulnerabilities. It details how various web technologies (ASP.NET, PHP, Python, etc.) handle duplicate parameters differently (e.g., first-wins, last-wins, concatenation). Use this skill during penetration testing to discover flaws in parameter parsing, which can lead to bypassing WAFs, performing logic manipulation, or achieving unauthorized access.

A comprehensive guide to diagnosing and enhancing search relevance within Qdrant. This skill addresses reported issues such as low precision, low recall, or irrelevant matches. It guides users through determining if the problem lies in the embedding model, Qdrant configuration, or the query strategy. Techniques covered include optimizing chunk splitting, tuning HNSW parameters, implementing hybrid search, and utilizing reranking for superior result quality.

Provides a systematic guide for diagnosing and improving poor search quality in vector databases like Qdrant. This guide covers troubleshooting issues such as low recall, when approximate search degrades, selecting optimal embedding models, and correctly tuning HNSW parameters, quantization, and filtering strategies. Essential for optimizing RAG and semantic search pipelines.

A comprehensive guide for diagnosing and resolving slow search performance in Qdrant. This resource covers issues related to low QPS (throughput), high latency for single queries, and slow filtered searches. Solutions include tuning HNSW parameters, managing memory pressure, implementing quantization, optimizing indexing, and configuring cluster settings for maximum efficiency.

This guide provides a comprehensive reference for common errors encountered when using the SerpApi. It covers issues like invalid API keys, exhausted search credits, missing parameters, and CAPTCHA blocks. Use this when your automated search results are incorrect, empty, or return unexpected status codes, allowing you to quickly diagnose the root cause and implement fixes.

This module provides essential abstractions and hooks (BuildParam, BuildParams, useBuildParams) for managing build parameters within the administrative interface. It allows developers to centralize the definition, retrieval, and usage of configuration parameters required for the application's setup and various features, ensuring clean and type-safe access to build-time variables.

This catalog provides critical abstractions for managing build-time configuration parameters within the Webiny API context. It offers `BuildParam` for accessing single configuration values and `BuildParams` for handling multiple parameters, ensuring that all API interactions utilize a structured, type-safe approach for development.

This catalog provides a comprehensive set of foundational abstractions for building robust, scalable applications. It includes standardized interfaces for interacting with AI models, managing key-value data stores, publishing domain events, structured logging, and handling build parameters. Developers can rely on these abstractions to ensure modularity and consistency across different service layers.

This skill provides a detailed guide on extending the Webiny Command Line Interface (CLI) by implementing custom commands. It utilizes the `CliCommandFactory` pattern to define structured commands, manage typed parameters, and execute complex logic. Use cases include automating data migrations, generating boilerplate code, executing custom deployment workflows, and performing CMS content exports.

This skill provides high-performance, real-time object detection using the Intel OpenVINO runtime. It operates via a Docker container, ensuring cross-platform compatibility. Supports detection across various Intel accelerators (NCS2, iGPU, Arc GPU) and CPUs. Users can customize parameters like confidence threshold, target classes, processing FPS, and model precision to optimize performance for specific hardware and accuracy needs.

This assistant guides users through managing Azure resources entirely via the command line using the Azure CLI (`az`). It identifies the correct commands, prompts for missing required parameters (like resource groups or locations), constructs the full command sequence, executes the action, and diagnoses any output errors to ensure successful deployment and configuration of services across Compute, Networking, and other Azure domains.

A comprehensive playbook for API reconnaissance and documentation review. Use this skill early in the testing process to enumerate all reachable endpoints, extract schemas, identify hidden versions (e.g., v1, v2, mobile), and discover undocumented parameters or fields across REST, GraphQL, and mobile APIs. Essential for mapping the full attack surface before deeper exploitation.