Skill UI

A comprehensive automation toolkit for managing Zendesk operations via Rube MCP. It provides workflows to list, search, create, update, and delete support tickets, manage user accounts (agents and end-users), and handle organization details. Ideal for integrating support workflows and automating customer service processes.

This guide enforces a mandatory, multi-stage process for debugging complex software issues. It moves developers beyond merely patching symptoms by forcing them through Root Cause Investigation, Pattern Analysis, Hypothesis Validation, and proper Implementation with testing. It is crucial for solving production bugs, failed tests, and performance issues in a structured manner.

This skill guides the parallel assignment of specialized agents when debugging multiple, independent failure domains. Instead of using one agent for all issues, isolate each problem (e.g., a specific test file or subsystem) to its own dedicated agent. This allows agents to work concurrently without sharing context or interfering with each other, significantly accelerating the debugging process and maintaining context purity.

This guide details advanced techniques for searching cricket matches by leveraging precise numerical scoring data. Instead of broad terms, users should utilize specific details—such as team totals (e.g., 168/9), runs off balls, wickets taken, or over details—combined with the match type and year to create highly targeted search queries. This method significantly improves search accuracy and efficiency when researching sports statistics.

This technique is used when the required answer in a case query is not directly stated but must be deduced by following a sequence of connected roles, people, or events. It involves mapping complex relationships, such as Victim -> Defendant -> Lawyer -> Witness, to trace indirect connections and reach the final piece of information. Ideal for advanced investigative research and deep knowledge graph traversal.

This skill teaches users how to optimize search queries for specific, structural information found within academic theses or dissertations. It emphasizes the critical need to include qualifying terms like "acknowledgment," "thesis," or "dissertation" in searches to successfully retrieve details about committee members, dedicating recipients, or other section-specific data, rather than just topic abstracts. This dramatically improves the relevance and accuracy of information retrieval.

Expert technique for narrowing down Asian drama candidates by leveraging streaming platform and broadcast channel information. Use this when the query mentions services like Netflix, Viki, or Amazon Prime, combined with genre and year details. This method significantly increases search precision, especially when combining platform data with temporal or thematic keywords.

This skill analyzes cultural clues within a query to determine the potential origin (e.g., Korean, Turkish, Indian, Thai) of a non-English TV drama. By identifying specific regional indicators—such as actor naming conventions, cultural themes, or broadcast channels—the system can generate highly precise, region-specific search keywords. This drastically improves search accuracy when the source country is not explicitly mentioned.

This skill is designed to facilitate communication and collaboration between different AI agents. Use it when you need to consult an expert agent, request a plan, seek a review, or continue a context-aware conversation with a specialized agent. It handles both real-time foreground chat and asynchronous background task submission, ensuring robust multi-agent workflows.

This guide teaches targeted verification strategies for historical research. When initial searches suggest a candidate name or figure, do not continue with broad searches. Instead, immediately switch to verifying the candidate against all specific constraints (time period, location, family details, major events) using precise search queries to confirm identity and eliminate false positives.

This guide details the operational workflow for namespace-scoped tenants within KubeSphere DevOps. It outlines how users without cluster-admin privileges can securely perform DevOps operations by strictly utilizing KubeSphere's dedicated APIs (`/kapis/`) and authenticating via OAuth tokens, ensuring strict resource isolation and access control within their designated namespace.

This skill guides users in analyzing complex questions related to criminal or legal incidents (e.g., murder, theft, arson, accident). By first classifying the specific case type and identifying domain-specific keywords, it dramatically improves the precision of subsequent search queries. It teaches users how to combine case type terms with distinctive constraints like amounts, dates, and locations for maximum search effectiveness.