Skill UI

A comprehensive core workflow for managing the full e-commerce lifecycle within Shopify. It utilizes the GraphQL Admin API to query order data, process fulfillments (including tracking), create draft orders, and search/manage customer records efficiently. Ideal for building robust order management systems and complex e-commerce integrations.

This comprehensive skill guides users through the entire lifecycle of developing AI agent skills. From initial concept (Understand) to structured design, writing the core skill logic, rigorous testing, and final performance optimization. It ensures skills are robust, accurate, and highly triggerable across any domain, including engineering, content creation, and research.

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 guide details a systematic methodology for identifying specific music tracks. Since searching solely by song title is often too generic, users must first establish constraints on the artist (e.g., nationality, birth year, genre, career type) to narrow the search space. Once the artist is identified, the search should focus on their discography, album tracklists, or specific release years to pinpoint the desired song.

This guide provides advanced search strategies for tracking Asian music, including K-pop, J-pop, and Filipino genres. It details how to construct highly specific queries by incorporating regional keywords, understanding idol comeback cycles, and utilizing cultural details (such as zodiac or national identity) to narrow down search results and avoid generic noise.

This technique guides users on how to use visual descriptions from music videos (MV), such as specific scenes, emotional themes (grief, loss), or real-world events, as powerful search anchors. Instead of only searching by title or artist, users can extract keywords from the visual narrative to refine search queries, significantly increasing the chances of identifying the correct song or tracing its origin. Ideal for music research and cultural analysis.

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 technique is used to locate a specific TV series by leveraging the known filmography of its creator (director, writer, or showrunner). When the question provides clues that the creator also worked on a distinct, identifiable project (e.g., a trilogy or an award-winning miniseries), use that secondary work as a powerful search anchor. Identify the person first using their other works, then trace back through their complete credits to pinpoint the target series.

TweetClaw provides comprehensive automation capabilities for X/Twitter using the Xquik REST API. It allows users to perform full read and write operations—including posting, replying, liking, following, and sending DMs. Key features include advanced tweet searching, bulk data scraping (23 tools), account monitoring, running structured giveaways, and composing algorithm-optimized content. Ideal for social media managers, digital marketers, and data analysts needing deep platform insights.

A comprehensive collection of core abstractions, event handlers, and use cases for building applications with a Headless Content Management System (CMS). It provides types for content entries, models, and groups, along with specific integrations for advanced search features like OpenSearch.

This module provides multiple standardized abstractions for interacting with the OpenSearch API. It includes dedicated abstractions for clients, factories, and operational contexts, allowing developers to implement robust, scalable, and type-safe interactions with OpenSearch within the webiny ecosystem. Use these patterns to ensure consistent data access regardless of the specific usage pattern.

This skill provides a powerful mechanism for modifying and extending AWS infrastructure using Pulumi handlers and dedicated declarative components. It allows developers to manage complex cloud setups, including configuring OpenSearch, VPC networking, resource tagging, custom domains, blue-green deployment strategies, and implementing environment-conditional configurations (e.g., production vs. development).