Skill UI

This skill wraps the `getCompactContext` functionality to efficiently retrieve a compacted ReasoningBank context, specifically optimized for cost-analysis queries. It generates a detailed report summarizing critical metrics such as tokens saved, memories retrieved, and agentic-flow availability. It is essential for monitoring and optimizing resource usage in complex AI workflows, providing deep visibility into the efficiency and cost of the context retrieval mechanism.

Automatically analyzes complex AI operations, including token usage patterns, model tier suitability, cache hit rates, and agent redundancy. It identifies potential waste and provides actionable, prioritized recommendations with estimated dollar savings to significantly reduce operational costs and improve efficiency across LLM pipelines.

A specialized audit skill designed to identify and quantify resource leakage, excessive costs, and billing vulnerabilities within complex development tool workflows (e.g., GitHub Apps). It traces webhook events, queue processing, and model calls to pinpoint where token burn or unauthorized resource usage is occurring, ensuring cost efficiency and clean billing practices.

A structured method for transforming experience (especially failures and complex tasks) into actionable, reusable knowledge. Instead of simple diary entries, this skill guides the user to extract root causes, identify underlying patterns, and articulate what they must do differently next time, thereby accelerating professional learning and debugging efficiency.

This skill provides robust automation capabilities for interacting with network devices via SSH using the industry-standard Netmiko library. It is designed to simplify complex network operations, such as configuration backups, status checks, and bulk management across heterogeneous devices, significantly improving operational efficiency.

This skill provides guidance on implementing common architectural patterns and best practices within the PyTorch framework. It is designed for developers building sophisticated deep learning models, helping to improve structure, efficiency, and code maintainability when working with neural networks.

This tool automatically converts design screenshots or visual exports into structured, functional Vue 3 Composition API components. It supports popular UI libraries like Vant, Element Plus, and Ant Design Vue. By batch converting screenshots, it streamlines the development process from raw design assets to reusable, production-ready code, significantly boosting frontend development efficiency.

This plugin provides advanced vector search capabilities using two distinct paths. The large-scale path supports millions of vectors via HNSW, ideal for general corpus search. The hot-path router handles small, critical pattern routing (≤11 patterns) with sub-ms latency. Key features include RaBitQ 1-bit quantization for memory efficiency (32× reduction), hyperbolic space search for hierarchical data, and unified cross-namespace search.

This skill is designed to audit and critique existing skill packages for their readiness, safety boundaries, resource efficiency, and evidence quality. It helps users diagnose concrete issues, such as incorrect triggers or insufficient evidence, and suggests improvements without applying any changes. Use it when you need a comprehensive audit or quality grade for a published skill.

This sophisticated tool optimizes marketing budget allocation across multiple channels using performance data, ROI calculations, and diminishing returns modeling. It analyzes current spend efficiency (ROAS, CPA) and generates a data-driven reallocation plan. Ideal for justifying spend shifts, maximizing investment returns, and creating phased implementation timelines for measurable growth.

This powerful tool provides real-time tracking and deep analysis of advertising spend across multiple connected platforms (Google, Meta, TikTok, etc.). It analyzes spending pacing against set targets, projects end-of-period spending, and flags overspend or underspend risks. Furthermore, it recommends data-driven budget reallocations based on efficiency metrics (CPA, ROAS) to maximize overall ROI for media buyers and marketing managers.

This tool performs deep, multi-touch attribution analysis to calculate comprehensive Return on Investment (ROI), Return on Ad Spend (ROAS), and Customer Acquisition Cost (CAC) across all marketing channels. It supports various attribution models (e.g., linear, time-decay) and projects long-term value using LTV, providing data for budget optimization, executive reporting, and identifying efficiency gaps.