Skill UI

Assistant for PostgreSQL developers that highlights native features, advanced data types, performance tuning patterns, and extension usage to optimize queries, indexes, and analytics in PostgreSQL projects.

This guide maps user questions and topics (e.g., configuration, memory, skills, CLI) to specific, relevant documentation paths and source code entry points within the QwenPaw ecosystem. It is designed for built-in QA Agents to eliminate aimless searching, ensuring the agent reads the most accurate files to provide comprehensive and precise answers about the system's features.

Comprehensive audit covering all aspects of web technical SEO, including crawlability (robots.txt, sitemaps), indexability, security headers, and URL structure. It deeply analyzes Core Web Vitals (LCP, INP, CLS) and assesses complex rendering scenarios like JavaScript SEO and structured data implementation for optimal search engine visibility.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.

Cross-database SQL performance optimization assistant offering query tuning, indexing strategies, pagination, batch operations, and monitoring guidance for MySQL, PostgreSQL, SQL Server, Oracle, and other relational systems.

Maintains the repository's llms.txt guidance file by auditing current documentation, specs, and structure to ensure the navigation summary matches reality and stays compliant with the official specification.

This skill automatically updates a markdown file with an index or table of files from a specified folder. It scans the target file, discovers files matching a pattern, and generates a structured list or detailed table. It supports simple lists, detailed tables, or categorized sections, preserving existing markdown formatting and using relative paths for links.

A comprehensive guide to setting up robust CI/CD pipelines for Algolia indexing. This includes running unit and integration tests against live indices, validating index settings against defined configurations, and implementing automated reindexing upon deployment (e.g., triggering on version tags). It ensures the stability and data consistency of your search service.

This utility collects comprehensive diagnostic evidence for Algolia support tickets or internal troubleshooting. It gathers index statistics, API key access control lists (ACLs), recent query logs, and network diagnostic information using API endpoints and shell scripting. Use it when diagnosing search performance or unexpected service behavior.

This comprehensive tutorial guides developers through setting up and utilizing Algolia for advanced search functionality. It covers fundamental operations such as indexing records using `saveObjects`, performing targeted searches, and configuring index settings (like custom ranking and faceting). The guide also demonstrates advanced use cases, including multi-index federation and browsing all records, making it ideal for developers building or optimizing a search backend.

This skill provides a comprehensive workflow for integrating external data sources into the Glean enterprise search platform. It covers setting up custom datasources, performing high-volume bulk document indexing using the Indexing API, and granularly managing document permissions (read/write access) to ensure accurate and secure search results for large organizations. Ideal for data engineers and developers building internal knowledge bases.

A comprehensive debug bundle designed to collect diagnostic evidence from Glean enterprise search integrations. It systematically checks datasource configuration, indexing status, search quality metrics, and connectivity logs. This tool is crucial for troubleshooting complex issues like connector failures, stale indexed data, and permission-based search gaps without needing direct admin console access.