Skill UI

Automates file format conversion guidance within data pipelines, covering ETL, workflow orchestration, data transformation, and streaming standards with production-ready examples.

This workflow provides the primary mechanism for converting complex, live websites into clean, LLM-ready markdown content. It supports single-page scraping using `scrapeUrl`, deep multi-page site crawling with `crawlUrl`, and scalable async crawling for large datasets. Ideal for building robust content ingestion pipelines and reliably extracting structured information from the web.

Firecrawl provides a comprehensive API for web data harvesting. It enables users to perform single-page scraping, multi-page crawling, site mapping (URL discovery), and advanced structured data extraction using Large Language Models (LLMs). Ideal for integrating data pipelines, building web monitoring tools, or conducting market research.

This skill manages the complete lifecycle of Fireflies.ai meeting transcripts. It allows users to fetch raw data, export in various formats (JSON, CSV, SRT), sanitize sensitive personal information (PII Redaction), and enforce data retention policies to ensure compliance with regulations like GDPR and CCPA. Ideal for data governance and compliance workflows.

This advanced workflow enables users to perform deep analyses on large-scale people intelligence datasets. Users can build custom queries with multi-dimensional filters, run comparisons across different candidate pools (e.g., Q1 vs Q4), and aggregate skill density by geographical region. It is essential for talent acquisition teams needing to identify market trends and optimize hiring strategies beyond standard search functions.

This bundle collects comprehensive diagnostic evidence from the Juicebox platform. It gathers API connectivity status, dataset health reports, analysis quota usage, and rate limit information into a single archive. Use it to systematically troubleshoot complex issues such as failed dataset uploads, stalled AI analysis runs, API authentication failures, or quota exhaustion.

This guide provides advanced strategies for optimizing interactions with the Juicebox AI API. It covers crucial best practices such as implementing caching mechanisms (with defined TTLs), executing batch operations for efficiency, managing rate limits, and optimizing data chunking for large datasets. Following these steps can significantly reduce end-to-end analysis time and ensure responsive, scalable data workflows.

Automates Kafka stream processor workflows within data pipelines, offering step-by-step guidance, best practices, production-ready code and configurations, and validation to support ETL, data transformation, workflow orchestration, and streaming data processing.

This tool provides comprehensive usage analytics and reporting for Kling AI video generation. It logs detailed events (submission, completion, errors) into structured JSONL files. Users can track performance metrics, analyze success rates, monitor total resource consumption (credits), and generate cost summaries over defined periods. Ideal for building dashboards, cost auditing, and understanding usage patterns.

This guide provides comprehensive patterns and best practices for designing high-impact Key Performance Indicator (KPI) dashboards. It covers everything from establishing a KPI framework (Strategic, Tactical, Operational) to defining departmental metrics (Sales, Marketing, Finance) and implementing best-practice layouts for executive summaries and SaaS metrics. Use this skill to translate raw data into actionable business insights.

This skill performs comprehensive research on public sentiment and discussion trends for any given topic over the last 30 days. It aggregates data and engagement from major platforms including Reddit, X, YouTube, TikTok, Hacker News, GitHub, and general web sources, providing a holistic view of current conversation and market reaction.

This guide details how to implement comprehensive observability for AI agents. It covers monitoring key metrics such as task success rates, step failures, execution duration, and credit consumption. Use this when setting up performance dashboards, configuring real-time alerts (via webhooks/Prometheus), or tracking agent reliability over time.