Skill UI

This skill provides comprehensive guidelines for monitoring Granola usage, tracking team meeting patterns, and building detailed analytics dashboards. It guides users in defining critical metrics (e.g., adoption rate, efficiency score) and establishing robust data pipelines. Users can stream meeting metadata from Granola to data warehouses like BigQuery, enabling deep, customizable reporting and automated weekly insights via services like Zapier and Slack.

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 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 skill provides comprehensive tracking and analysis of OpenRouter API usage metrics. It collects critical data points such as per-request total cost, prompt and completion token counts, latency, and usage patterns. Use this skill when building financial dashboards, optimizing AI spending, monitoring API consumption, or generating detailed usage reports.

This skill analyzes proxy access logs, DNS query logs, and network flow data to identify unauthorized SaaS and cloud services (Shadow IT). It uses Python and pandas to aggregate traffic, classify domains against known SaaS categories, and calculate risk scores based on data volume and user count. Ideal for conducting thorough security audits and generating actionable remediation reports.

This skill provides a comprehensive framework for evaluating Power BI reports. It assesses report quality, usage adoption rates, performance metrics, and structural integrity across different lifecycle stages (development, testing, active use). It analyzes usage data, audience reach, and performance bottlenecks, generating actionable feedback and optimization recommendations to ensure reports are effective and maintainable.