Skill UI

Manages FairDB PostgreSQL backups via pgBackRest and Wasabi S3, automating scheduling, integrity verification, PITR restores, monitoring, and compliance reporting for resilient disaster recovery.

This skill provides comprehensive APIs and patterns for managing AI models, tracking usage, and handling pricing structures within a platform environment. It is essential for developers needing to integrate robust model lifecycle management, usage monitoring, and billing logic into their applications.

Run targeted file path traversal assessments to find directory traversal and LFI vulnerabilities across web parameters, verify exploitation payloads, and document sensitive files exposed via automated fuzzing and manual checks.

Performs a structured, multi-phase audit on local branch changes (diffs) to identify security vulnerabilities, bugs, and code quality issues. It systematically checks for common risks like Injection (SQL, XSS), Broken Authentication, IDOR, CSRF, and business logic flaws, providing detailed severity, evidence, and suggested fixes. Ideal for pre-merge code reviews and security audits.

Scans infrastructure-as-code, application, and system configurations via the security-misconfiguration-finder plugin to expose vulnerabilities and compliance gaps, enabling proactive remediation before deployment.

Scans Android APKs for Firebase misconfigurations, testing databases, storage, authentication, and cloud functions to surface vulnerabilities during mobile security audits.

This skill guides the end-to-end development, deployment, and secure integration of complex AI features into Firebase applications. It covers setting up Cloud Functions, Firestore/Storage rules, Authentication, and connecting robustly with Vertex AI/Gemini for advanced AI capabilities. Focuses on building production-grade, highly secure, data-intensive AI systems.

A systematic guide for debugging complex, hard-to-diagnose issues with Firecrawl. Use this when standard troubleshooting fails, such as when scrapes return empty content, crawl jobs hang indefinitely, or webhooks fail to fire. It employs layer-by-layer isolation techniques, covering API connectivity, target URL accessibility, and content quality to pinpoint failure points.

Provides comprehensive observability patterns for Firecrawl web scraping operations. It covers key metrics such as scrape success rates, credit consumption tracking, content quality assessment, and latency monitoring. Use this skill for implementing robust monitoring dashboards, setting up proactive failure alerts, and optimizing the reliability of web crawling workflows.

This skill provides robust, automated guardrails for web scraping pipelines using Firecrawl. It enforces critical policies to ensure compliance and stability, including domain blocklists (preventing scraping prohibited sites), managing API credit budgets, filtering low-quality content (e.g., error pages, thin content), and implementing granular per-domain rate limiting. Use this when building highly reliable, legal, and cost-efficient scraping solutions.

A comprehensive guide to implementing production-grade reliability patterns for web scraping pipelines using Firecrawl. Learn techniques such as circuit breakers, crawl fallbacks, content quality validation, and robust backoff strategies to handle timeouts, API failures, and inconsistent data quality, ensuring maximum uptime and data integrity.

This skill provides deep web scraping capabilities, allowing users to extract complex content, take screenshots, and parse PDFs from web pages. It handles advanced interactions like clicking and scrolling, making it ideal for detailed data gathering, batch URL processing, and complex web content analysis.