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Found 92 Skills
Use when user input contains xlb topic queries (for example "xlb >vibe coding/vib", "xlb ??vibe coding", or "查询xlb vibe coding主题") and the task is to fetch Markdown index from local getPluginInfo API, then perform code-based retrieval with routing to available network skills/MCP tools when possible.
Continuous communication channel via MCP AI Interaction tool. Activate with 'khởi động ai_interaction'. Enables real-time Vietnamese conversation with action-first principle - execute first, explain minimally.
Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
Debug failed Render deployments by analyzing logs, metrics, and database state. Identifies errors (missing env vars, port binding, OOM, etc.) and suggests fixes. Use when deployments fail, services won't start, or users mention errors, logs, or debugging.
Automatically discover MCP (Model Context Protocol) skills when building MCP servers, designing tools, implementing resources/prompts, or testing MCP integrations. Activates for MCP server development tasks.
Uncertainty-aware non-linear reasoning system with recursive subagent orchestration. Triggers for complex reasoning, research, multi-domain synthesis, or when explicit commands `/nlr`, `/reason`, `/think-deep` are used. Integrates think skill (reasoning), agent-core skill (acting), and MCP tools (infranodus, exa, scholar-gateway) in recursive think→act→observe loops. Uses coding sandbox for execution validation and maintains deliberate noisiness via NoisyGraph scaffold. Supports `/compact` mode for abbreviated outputs and `/semantic` mode for rich exploration.
Checks if a specific service is available at a given address.
This skill should be used when the user asks to "design agent tools", "create tool descriptions", "reduce tool complexity", "implement MCP tools", or mentions tool consolidation, architectural reduction, tool naming conventions, or agent-tool interfaces.
Use this skill when querying Tarkov game data via MCP tools. Provides optimal query patterns, data relationships, and best practices for the tarkov-dev and eft-wiki MCP servers.
Interactive assistant for creating new Claude commands with proper structure, patterns, and MCP tool integration
Multi-agent orchestration workflow for deep research: Split a research objective into parallel sub-objectives, run sub-processes using Claude Code non-interactive mode (`claude -p`); prioritize installed skills for network access and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + summary of key conclusions/recommendations". Applicable scenarios: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-agent parallel research/multi-process research".
Send assistance requests to an assistant, applicable to task scenarios such as Chinese cultural understanding, classical Chinese text comprehension, creation of Chinese characteristic works, writing promotion copy for Xiaohongshu and Douyin, writing test cases, information retrieval, etc. It is also a strong substitute and assistant for other expert assistants, and can be used as an alternative backup solution for most tasks.