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nodetool
nodetool には nodetool-ai から収集した 15 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
Create and configure NodeTool agent YAML configs, set up agent tools, system prompts, planning agents, and workspace isolation. Use when user asks to create an agent config, write YAML for an agent, configure agent tools, set up autonomous execution, or work with the agent CLI.
Use NodeTool REST API, WebSocket protocol, Chat API (OpenAI-compatible), workflow execution endpoints, and streaming responses. Use when user asks about API endpoints, WebSocket protocol, how to call the API, build a client, integrate with NodeTool, or stream workflow results.
Create browser automation agents that navigate websites, extract data, fill forms, and perform multi-step web tasks using natural language instructions. Use when user asks to automate browsing, scrape websites with AI, build a web agent, or perform complex browser interactions.
Use NodeTool chat CLI commands, interactive terminal, agent mode, workspace management, and Global Chat features. Use when user asks about chat commands, interactive terminal, chat features, agent mode in chat, or the Global Chat interface.
Create custom NodeTool nodes, implement BaseNode subclasses, use @prop decorators, build node packages with process/genProcess methods, register nodes, handle media refs and secrets. Use when user asks to create a node, add a node type, build a custom node, implement a processor, or extend NodeTool with new functionality.
Deploy NodeTool servers using Docker, SSH, RunPod, GCP, or Supabase. Use when user asks to deploy, host, set up a server, configure Docker, use RunPod/GCP/Supabase, manage deployment.yaml, or configure environment variables for production.
Configure AI model providers (OpenAI, Anthropic, Gemini, Ollama, HuggingFace, FAL, Replicate), set up API keys, choose models by task, run local inference with llama.cpp/MLX. Use when user asks about models, providers, API keys, which model to use, or configure any AI provider.
Set up RAG pipelines, vector indexing, document ingestion, vector search, and knowledge base creation in NodeTool. Use when user asks about RAG, document indexing, vector search, chat with documents, knowledge base, embeddings, or collection management.
Debug NodeTool workflow failures, node errors, performance issues, stuck executions, type mismatches, and deployment problems. Use when user reports a bug, workflow failure, node error, performance issue, stuck execution, or needs help diagnosing any NodeTool problem.
Build and edit NodeTool visual workflows using UI tools. Use this skill whenever the user asks to create a workflow, connect nodes, build a pipeline, add nodes to a graph, generate images/video/audio via workflows, or asks about workflow patterns. Also use when the user mentions node types, data flow, or wants to automate any multi-step process in NodeTool.
Strip "AI slop" from code and prose in this repo — over-engineered abstractions, defensive checks on trusted paths, narrating comments, dead error handlers, redundant types, useEffect-for-derived-data, raw MUI imports, whole-store Zustand subscriptions, throat-clearing prose. Use when reviewing your own diff before commit, when the user says "unslop this", or when refactoring AI-generated code in `web/`, `electron/`, `mobile/`, or `packages/`. Triggers on TypeScript/React/Zustand/MUI/TanStack Query files. Tailored to NodeTool's stack (React 19, Zustand 5, MUI v7 + ui_primitives, TanStack Query v5, Vitest/Jest, Drizzle).
Companion CLIs for Runpod workflows — HuggingFace, GitHub, Docker, and AWS.
runpod-flash SDK and CLI for deploying AI workloads on Runpod serverless GPUs/CPUs.
Runpod CLI to manage your GPU workloads.
Playwright E2E testing patterns, Page Object Model, configuration, CI/CD integration, artifact management, and flaky test strategies.