Skill UI

This workflow systematically analyzes deployed AWS resources and Infrastructure-as-Code (IaC) definitions. It collects usage metrics from CloudWatch and Cost Explorer to identify over-provisioning, unused resources, and inefficient configurations (e.g., right-sizing EC2, S3 lifecycle policies). It generates actionable cost optimization recommendations and creates structured GitHub issues for tracking and implementing savings.

This skill designs and audits the core engineering harness required for reliable AI agent collaboration within a codebase. It establishes critical infrastructure elements such as change tracking, linting rules, CI/CD gates, and standardized documentation, ensuring the repository remains the single source of truth for all intelligent agents. Ideal for setting up complex development workflows.

Automatically generates a comprehensive, tabbed status page (artifact) for large-scale, multi-workstream projects. Ideal for tracking long-running initiatives like software migrations or major launches, providing a single source of truth covering background, plan, risks, and decisions. It generates a shareable, self-contained HTML page and supports delta reporting for easy updates.

A comprehensive Notion dashboard designed for real-time team operations and performance tracking. It provides a centralized overview by aggregating Key Performance Indicators (KPIs) in a grid format, displaying 7-day trend sparklines, showing live activity feeds, and summarizing tasks in a structured database table. Ideal for project managers and team leads who need a single source of truth for project status and team coordination.

This skill consumes federation_spend events to aggregate per-peer spending across rolling time windows (1h, 24h, 7d). It implements a crucial circuit breaker mechanism by monitoring if any peer's spending exceeds a predefined threshold, ensuring the stability and resource management of the federation. Used to establish spending baselines and verify budget constraints.

This tool generates a detailed cost report, tracking token usage and associated USD costs across all AI agents and models. It provides crucial insights into budget utilization, breaking down spending by model (e.g., Opus, Sonnet), agent, and operational tier (Tier 1/2/3), helping teams manage spending and optimize resource allocation.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

Search and analyze trending topics across Chinese and international sources like Bing, Google, HackerNews, Weibo, and Bilibili. Useful for tracking breaking news, monitoring keywords, and generating hotspot reports.

This tool performs deep customer cohort analysis to understand retention patterns, lifetime value (LTV), and the long-term impact of various acquisition channels and initial behaviors. Users can segment customers by time, source, or revenue tier to identify high-value groups, optimize onboarding, and improve overall customer retention strategies. Ideal for SaaS, eCommerce, and B2B businesses tracking customer lifecycle.

A comprehensive guide to constructing rigorous empirical datasets for academic papers in finance and banking. It covers best practices for handling complex data sources (e.g., bank micro-data, central bank reports, macro series), addressing measurement biases, and ensuring full replicability, adhering to the standards of top-tier economic journals. Focus areas include merger tracking, regime transitions, and variable definition consistency.