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Found 173 Skills
Refine and restructure existing notes into well-organized, deduplicated, and enriched documents in your personal Yuque knowledge base. For personal/individual use — reads and writes your own docs.
WPS Writer Intelligent Assistant, which controls Word documents through natural language to solve pain points such as typesetting, formatting, and content editing
Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"
Agent skill for authentication - invoke with $agent-authentication
Interactive assistant for creating new Claude commands with proper structure, patterns, and MCP tool integration
Run Ruflo background workers using Claude Code native /loop scheduling
Create and manage prompt snippets — reusable text blocks referenced inside AI Config variation prompts. Keeps common instructions, personas, and guardrails consistent across multiple configs.
Workflow and best practices for writing Apache Airflow DAGs. Use when the user wants to create a new DAG, write pipeline code, or asks about DAG patterns and conventions. For testing and debugging DAGs, see the testing-dags skill.
Agent Mail inbox monitoring. Check pending messages, HELP_REQUESTs, and recent completions. Triggers: "inbox", "check mail", "any messages", "show inbox", "pending messages", "who needs help".
Manage YuQue knowledge base documents via the YuQue MCP tool. Suitable for creating, searching, updating, moving or deleting YuQue documents; organizing knowledge base structure; batch document operations; managing document templates; and implementing collaborative workflows. Provides MCP tool integration modes and key usage points.
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.
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".