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Found 7,093 Skills
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.
Orchestrates end-to-end video generation through sequential workflow steps (audio, direction, assets, design, coding). Activates when user requests video creation from a script, wants to resume video generation, mentions "create video", "generate video", or "video workflow", requests running a specific step (audio, direction, assets, design, coding), asks to "create audio", "generate direction", "create assets", "generate design", or "code video components", or wants to resume a video. Manages workflow state tracking and parallel scene generation.
Orchestrator for WebView UI mockup workflow - delegates design iteration to ui-design-agent and implementation scaffolding to ui-finalization-agent. Use when user mentions UI design, mockup, WebView interface, or requests 'design UI for [plugin]'.
Parallel development workflow using git worktrees. Prepare isolated worktree directories and execute tasks across multiple workspaces for concurrent feature development.
This skill guides systematic code refactoring following the DRY (Don't Repeat Yourself) principle. Use it when users request to eliminate code duplication, refactor repetitive code, apply the DRY principle, or mention code smells like copy-paste code, magic numbers, or repeated logic. It implements a 4-step workflow from identifying repetition to verified refactoring.
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.
Global integrated development and collaboration workflow skill that covers the entire lifecycle stages including requirement evaluation, development, testing, quality assurance, documentation, submission, and release. It can integrate all basic atomic skills to realize PDTFC+ cycle automation and optimize division of labor and cooperation.
Configure kata workflow toggles and model profile. Triggers include "settings".
Generates valid n8n workflow JSON with nodes, connections, settings, credentials. Use when creating workflow automations programmatically, scaffolding AI agent workflows with LangChain nodes, or converting requirements into n8n JSON.
Guide for creating Standard Operating Procedures and SOPs and composite workflows by combining atomic Agent Skills. Use when users want to design, structure, or implement multi-step workflows that orchestrate multiple skills for complex business goals. Transforms loose tool collections into reliable, repeatable business processes.
LangGraph checkpointing and persistence. Use when implementing fault-tolerant workflows, resuming interrupted executions, debugging with state history, or avoiding re-running expensive operations.
Use this skill when working with scientific research tools and workflows across bioinformatics, cheminformatics, genomics, structural biology, proteomics, and drug discovery. This skill provides access to 600+ scientific tools including machine learning models, datasets, APIs, and analysis packages. Use when searching for scientific tools, executing computational biology workflows, composing multi-step research pipelines, accessing databases like OpenTargets/PubChem/UniProt/PDB/ChEMBL, performing tool discovery for research tasks, or integrating scientific computational resources into LLM workflows.