Skill UI

This tool facilitates comprehensive prior art searches across global patent databases (Google Patents, Espacenet) and academic literature (Google Scholar, arXiv). It guides users through extracting core inventive concepts, performing targeted searches using keywords and IPC/CPC codes, and analyzing the results to assess novelty, overlap risk, and general freedom-to-operate.

This internal agent skill defines a systematic, multi-step procedure for scanning GitHub repositories to gather comprehensive evidence supporting or explaining bug clusters. The process covers searching open issues, inspecting recent commits, analyzing code paths, and checking deployment history. It assigns evidence confidence tiers (Exact, Strong, Moderate, Weak) to provide a deep, actionable understanding of potential software defects.

This skill provides comprehensive diagnosis and optimization for agent skill libraries. By analyzing historical session transcripts from platforms like Claude Code and Codex, alongside static skill file checks, it scores each skill across 8 dimensions. It identifies issues such as low trigger rates, poor post-invocation user reaction, and incomplete workflow execution, generating a prioritized report (P0/P1/P2) to significantly improve the agent's overall performance and reliability.

A comprehensive guide for deep debugging complex Snowflake issues. This guide covers advanced techniques including detailed query profiling (spill analysis), diagnosing lock contention and transaction conflicts, analyzing metadata operations, and optimizing partition usage. Use it when standard troubleshooting fails to address slow queries or warehouse performance bottlenecks.

A comprehensive guide to optimizing query performance in Snowflake. Learn advanced techniques such as implementing clustering keys, utilizing materialized views, leveraging result caching, and analyzing query profiles. This guide also covers best practices for warehouse tuning and optimizing common SQL anti-patterns to ensure efficient data querying and cost management.

This skill performs a structured Systematic Literature Review (SLR) by analyzing multiple academic papers on a given topic. It searches academic databases (like arXiv), extracts structured metadata (research questions, methodologies, key findings, limitations) from the entire set of papers, and synthesizes overarching themes and research trends. It is ideal for creating comprehensive literature surveys, annotated bibliographies, and cross-paper comparisons, outputting reports in professional citation formats like APA, IEEE, or BibTeX.

This technique is designed for the final verification stage when analyzing a candidate TV series. Instead of accepting initial matches, users must perform targeted searches combining the show name and specific character details (e.g., birth year, specific plot event, relationship). This ensures that the candidate show satisfies all complex constraints, eliminating false positives and confirming the accuracy of the plot details.

This guide outlines best practices and structured workflows for automating complex tasks within the Unity Editor using the Model Context Protocol (MCP). It provides programmatic methods for managing GameObjects, applying script edits, analyzing the editor state, executing batch commands, and capturing detailed, multi-view screenshots. Ideal for developers needing robust, repeatable, and automated testing or operational tasks within Unity projects.

Generates a comprehensive, single-screen financial report in a self-contained HTML file. This skill is designed for analyzing key business metrics, including P&L summaries, MRR trends, KPI cards (Revenue, Gross Margin, Cash Runway), and top-accounts analysis. Ideal for quarterly or monthly financial reviews in SaaS or startup environments.

This comprehensive, zero-trust security auditor scans third-party AI agent skills before installation. It performs a rigorous 6-phase review process, analyzing surface patterns, script integrity, permissions, and supply chain risks. It is designed to detect malicious payloads, credential theft, instruction overrides, and prompt injection attacks, ensuring secure AI development and deployment.

Methodology for capturing, analyzing, and replaying LoRaWAN and sub-GHz wireless traffic. Useful for testing IoT deployments, fixed-code remotes, garage doors, TPMS, and other devices in 433/868/915 MHz bands.

This comprehensive playbook guides the testing of Cross-Origin Resource Sharing (CORS) misconfigurations. It focuses on detecting critical vulnerabilities such as reflected origins, wildcard trust misuse, credentialed cross-origin reads, and bypasses in origin allowlists. Use this when analyzing browser-based access and trust boundaries for authenticated APIs.