「terminal」の検索結果

Audit Wi-Fi networks with the aircrack-ng suite. Use when a user asks to test their own wireless network, capture WPA2 handshakes, crack captured handshakes offline, put an adapter into monitor mode, or perform a wireless pentest under an authorized engagement.

日本語の概要は準備中です。原文の説明を表示しています。

You are an expert in the Vercel AI SDK, the TypeScript toolkit for building AI-powered applications. You help developers integrate LLMs (OpenAI, Anthropic, Google, Mistral, Ollama) with React Server Components, streaming UI, tool calling, structured output with Zod schemas, RAG pipelines, multi-step agents, and edge-compatible AI features — the standard way to add AI to Next.js, Nuxt, SvelteKit, and any Node.js app.

日本語の概要は準備中です。原文の説明を表示しています。

Activepieces is an open-source workflow automation platform with a visual builder, 400+ integrations ("pieces"), code steps, branching, loops, and webhooks. Use when a user asks to self-host a Zapier or n8n alternative, automate workflows with a no-code builder, build a custom integration piece, or set up open-source business automation.

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Build AI agents that automate scientific research — hypothesis generation, experiment design, data analysis, and paper writing using agentic tree search. Use when: automating research workflows, generating and testing hypotheses, building AI-powered research assistants.

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Expert guidance for Apache Arrow, the cross-language columnar memory format for analytics workloads. Helps developers use Arrow for high-performance data interchange between systems, zero-copy reads, and efficient columnar processing in Python (PyArrow) and JavaScript (Arrow JS).

日本語の概要は準備中です。原文の説明を表示しています。

Run AI agent and LLM evaluations in CI/CD pipelines — automated quality gates that fail the build when AI output quality drops. Use when someone asks to "test my AI agent", "add evals to CI", "catch prompt regressions", "compare models", "evaluate LLM output quality", "set up AI quality gates", or "benchmark my agent before deploying". Covers eval frameworks (Cobalt, Promptfoo, Braintrust), LLM-as-judge scoring, threshold-based assertions, and GitHub Actions integration.

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Implement safety guardrails for AI systems — content filtering, prompt injection detection, output validation, bias mitigation, and responsible AI practices. Use when tasks involve adding safety layers to LLM applications, detecting prompt injection attacks, filtering harmful content, implementing rate limiting for AI APIs, validating LLM outputs against schemas, building moderation pipelines, or ensuring AI systems comply with safety policies.

日本語の概要は準備中です。原文の説明を表示しています。

Actix Web is a powerful, high-performance web framework for Rust. It provides async handlers, type-safe extractors, middleware, and integrates with the Rust ecosystem for building fast, reliable, and memory-safe web services.

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Run autonomous AI-driven penetration tests on web applications using tools like Shannon, PentAGI, and similar frameworks. Use when tasks involve setting up automated penetration testing pipelines, combining AI agents with security tools (nmap, subfinder, nuclei, sqlmap), building autonomous exploit chains, generating pentest reports with proof-of-concept exploits, or integrating AI pentesting into CI/CD pipelines. Covers the full pentest lifecycle from reconnaissance to reporting using AI orchestration.

日本語の概要は準備中です。原文の説明を表示しています。

Covers scripting Autodesk 3ds Max, the 3D modeling and rendering application, with MAXScript and Python (pymxs): scene manipulation, object creation, material assignment, camera and light setup, batch operations, and file I/O. Use when tasks involve automating repetitive 3ds Max workflows, batch processing scenes, running scripts headless with 3dsmaxbatch, creating custom tools, or scripting scene setup for archviz, product visualization, or VFX.

日本語の概要は準備中です。原文の説明を表示しています。

Configuration management and automation with Ansible. Use when the user needs to write playbooks, manage inventory, create roles, use Ansible Vault for secrets, or orchestrate multi-server deployments across environments.

日本語の概要は準備中です。原文の説明を表示しています。

Automate online content creation and monetization with AI — blog posts, videos, social media, affiliate marketing, and digital products. Use when: building passive income streams with AI, automating content marketing, scaling content production.

日本語の概要は準備中です。原文の説明を表示しています。

3proxy is a small open-source proxy server that runs HTTP/HTTPS, SOCKS4/5, SNI and TCP/UDP port-mapping proxies from one config file. Use when a user asks to set up an HTTP or SOCKS5 proxy, add proxy users and passwords, write 3proxy access rules, chain or rotate upstream (parent) proxies, limit bandwidth, connections or monthly traffic per user, run 3proxy in Docker, or fix a 3proxy.cfg that will not start.

日本語の概要は準備中です。原文の説明を表示しています。

Audit web pages and components for WCAG 2.2 accessibility compliance. Use when a user asks to check accessibility, find a11y issues, audit for WCAG compliance, fix screen reader problems, check color contrast, ensure keyboard navigation works, or prepare for accessibility regulations like the European Accessibility Act or ADA.

日本語の概要は準備中です。原文の説明を表示しています。

Generate complete presentations with AI — from outline to polished slides. Use when a user asks to create a presentation, build slides, make a pitch deck, generate a slide deck, create a keynote, prepare a talk, build a demo presentation, or produce any slide-based content.

日本語の概要は準備中です。原文の説明を表示しています。

Runs GitHub Actions workflows on your own machine in Docker containers with act, so CI can be tested without pushing. Use when a user asks to test GitHub Actions workflows locally, debug a failing CI pipeline, pass secrets or inputs to a local run, or run workflows offline.

日本語の概要は準備中です。原文の説明を表示しています。

Build and trace AI agents in Python with AgentScope, an open-source agent framework with a ReAct loop, tools, middleware, team pipelines and OpenTelemetry tracing. Use when building production agents that need observability, debugging an agent's model and tool calls, capping token spend per reply, or coordinating a leader with specialist agents.

日本語の概要は準備中です。原文の説明を表示しています。

Builds full-stack web applications with AdonisJS — a batteries-included Node.js framework with ORM, auth, validation, and mailer built-in. Use when someone asks to "build a web app with Node.js", "Laravel for Node.js", "full-stack Node framework", "AdonisJS", "batteries-included backend", or "Node.js with built-in ORM and auth". Covers Lucid ORM, auth (sessions, tokens, social), VineJS validation, Edge templates, and deployment.

日本語の概要は準備中です。原文の説明を表示しています。

Angular is Google's TypeScript-based frontend framework for building scalable single-page applications. It provides components, dependency injection, RxJS-based reactivity, routing, forms, HTTP client, and a powerful CLI for development.

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AG-UI (Agent-User Interaction Protocol) is an open, event-based protocol that streams an AI agent's text, tool calls, state and lifecycle events to a frontend over HTTP and Server-Sent Events. Use when the user wants to build an AG-UI server, connect an agent or framework (LangGraph, Mastra, CrewAI, Pydantic AI) to a React or custom UI, stream agent progress and state, or use CopilotKit with AG-UI.

日本語の概要は準備中です。原文の説明を表示しています。

AG2 (formerly AutoGen) is an open-source Python framework for building AI agents and multi-agent systems that use tools, human approval and structured conversations. Use it when you need agents that call functions, collaborate in a group chat, execute code, or when you are migrating AutoGen or pyautogen code to AG2 v1 or ag2-classic.

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Builds Agent2Agent (A2A) servers and clients, the open protocol (originally from Google, now under the Linux Foundation) that lets AI agents from different frameworks call each other. Use when the user wants to create an A2A-compliant agent, build an Agent Card, implement task management, connect agents across frameworks, set up agent discovery, handle streaming responses, implement push notifications, or orchestrate multi-agent workflows. Trigger words: a2a, agent to agent, agent2agent, a2a protocol, a2a server, a2a client, agent card, agent interoperability, agent collaboration, multi-agent, agent discovery, a2a sdk, a2a task.

日本語の概要は準備中です。原文の説明を表示しています。

Aceternity UI is a collection of animated React components (3D cards, spotlight, background beams, moving borders, wavy backgrounds) built with Tailwind CSS and the motion library, installed into your project as source through the shadcn CLI. Use when someone asks for "animated hero section", "3D tilt card", "spotlight effect", "moving border button", "Aceternity component", or "glowing background" in a React or Next.js app.

日本語の概要は準備中です。原文の説明を表示しています。

Add persistent memory to AI coding agents — file-based, vector, and semantic search memory systems that survive between sessions. Use when a user asks to "remember this", "add memory to my agent", "persist context between sessions", "build a knowledge base for my agent", "set up agent memory", or "make my AI remember things". Covers file-based memory (MEMORY.md), SQLite with embeddings, vector databases (ChromaDB, Pinecone), semantic search, memory consolidation, and automatic context injection.

日本語の概要は準備中です。原文の説明を表示しています。