「computer」の検索結果

Control Agent Zero's Docker/Xpra desktop and GUI apps; not the user's host computer.

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。

Guide safe use of code_execution_remote for shell-backed execution on the connected A0 CLI host. Use when the user asks for their computer, local terminal, CLI host, remote shell, not Docker, or host-side Python/Node/terminal commands.

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。

Guide safe use of text_editor_remote for reading, writing, and patching files on the connected A0 CLI host. Use when the user asks to inspect or edit files on their computer, local files, CLI host files, or files that are explicitly not Docker/server files.

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。

macOS system performance diagnostics — see how the machine is running and what's slowing it down: CPU/GPU/memory/energy hogs, thermal throttling, memory and swap pressure, disk usage, Spotlight indexing, launchd/startup load, via a deterministic read-only CLI with known-process interpretation (kernel_task, WindowServer, mds_stores). USE WHEN mac slow, system slow, what's slowing down my mac, computer is slow, what's eating CPU, CPU usage, GPU usage, what's using the GPU, memory pressure, RAM usage, swap, runaway process, fans loud, mac running hot, thermal throttling, system health, check my mac, how's my system running, top processes, energy hogs, activity monitor, startup items, launch agents load, system taxed. NOT FOR network/wifi diagnostics, website or deployed-app health monitoring, or security scanning.

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。

Scrapes social platforms, business data, and e-commerce via Apify actors — Instagram, LinkedIn, TikTok, YouTube, Facebook, Google Maps, Amazon, and web crawls — filtering in code. USE WHEN scrape Instagram, scrape LinkedIn, scrape TikTok, scrape YouTube, scrape Facebook, Google Maps leads, Amazon reviews, business intelligence, multi-platform social listening, competitive analysis, lead generation, social monitoring, Apify actors, web crawl, extract contacts. NOT FOR X/Twitter account operations like posting, threads, or bookmarks (those need a dedicated X API client), 4-tier progressive scraping with proxy escalation (use BrightData), or real-Chrome bot bypass and computer use (use Interceptor).

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, refactor, and test LangBot platform adapters for the Event-Based Agents architecture. Use when adding or migrating Telegram, Discord, or other messaging platform adapters to the EBA adapter layout, validating unified event/message conversion, writing live adapter probes, or using standalone plugin runtime plus Computer Use for end-to-end platform testing.

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。

Prepare a local LangBot development and testing environment for an AI agent. Use when setting up WSL or Linux development, shared local URL variables, proxy variables, backend/frontend startup, Playwright MCP browser access, GitHub OAuth browser login, persisted Chrome profiles, or future Codex computer-use environment paths.

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 the computer-use-demo image and drive the Streamlit UI headlessly to verify changes end-to-end.

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。

Guide a new user through their first computer-use agent run (env check, safe browser-only task, then open the trajectory viewer).

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。

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says \"DSE\", \"design space exploration\", \"sweep parameters\", \"optimize\", \"find best config\", or wants iterative parameter tuning.

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。

Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says "DSE", "design space exploration", "sweep parameters", "optimize", "find best config", or wants iterative parameter tuning.

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。

Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

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。

Work with GitHub and GitLab repositories through resident gh/glab/git auth on the agent computer.

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。

Publish a long-lived internal web app, site, or dashboard from the agent computer. Scope-bound (only the owner's scope, plus whoever you share it with, can reach it), immutable versions with rollback, a stable friendly link. No public URL.

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。

Operate the user's real desktop apps and windows on macOS, Windows, or Linux. Use when the user asks to open or drive a native app, click or type in a desktop UI, inspect or arrange a window, use their signed-in system browser, or verify an end-to-end GUI flow, including "open Settings and turn on dark mode", "click Save in that window", "what's on screen". Uses an accessibility-first driver (Cua Driver by default, Peekaboo on macOS). Not for Superset's in-app browser pane, headless scraping, or anything an API or CLI can do directly.

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。

Foundation model for image segmentation with zero-shot transfer. Use when you need to segment any object in images using points, boxes, or masks as prompts, or automatically generate all object masks in an image.

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。

State-of-the-art text-to-image generation with Stable Diffusion models via HuggingFace Diffusers. Use when generating images from text prompts, performing image-to-image translation, inpainting, or building custom diffusion pipelines.

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。

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

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。

Use Transformers.js to run state-of-the-art machine learning models directly in JavaScript/TypeScript. Supports NLP (text classification, translation, summarization), computer vision (image classification, object detection), audio (speech recognition, audio classification), and multimodal tasks. Works in browsers and server-side runtimes (Node.js, Bun, Deno) with WebGPU/WASM using pre-trained models from Hugging Face Hub.

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。

Profile, audit, and optimize frontend page performance with emphasis on animation work, memory-leak risks, long-session slowdowns, CSS animations, canvas/WebGL requestAnimationFrame loops, marquees, skeletons, GSAP/Three/Matter effects, timers, listeners, and observers. Use when the user asks to make animations performant, pause offscreen animations, look for memory leaks, profile pages that slow the computer over time, fix janky scrolling, reduce CPU/GPU use, or repeat the "only play in view" optimization on React/Vite/Next/frontend pages using Codex Browser.

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。

Use when a user asks what SenseNova Team Harness is, wants an introduction or overview, is getting started, or is deciding whether it fits — a self-hosted workspace where people and local AI agents collaborate on conversations, projects, work items, and artifacts. Covers its core concepts (Workspace, Project, Conversation, Agent, WorkItem, Resource, Artifact, Local Computer), main capabilities, how to run it, and the basic usage flow.

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。

Use Peekaboo for macOS screenshots, Accessibility inspection, and background app/window/UI automation, including fallback computer use when the primary tool cannot handle an authorized 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。

Hunt NTLM/Negotiate information disclosure on internet-reachable IIS/SharePoint/Exchange. Anonymous NTLM Type-2 challenge capture leaks NetBIOS domain, internal DNS forest, computer name, AD timestamp via AV_PAIRS structure. Default Windows-installer hostnames (WIN-XXXXXXXXXXX pattern) signal lazy provisioning. Use when target advertises `WWW-Authenticate: NTLM` or `Negotiate` headers anonymously.

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。

Use when the user asks to "generate daily paper", "search arXiv for EEG papers", "find EEG decoding papers", "review brain-computer interface papers", or wants to create paper summaries for EEG/brain decoding/speech decoding research. This skill automates searching arXiv for recent papers on EEG decoding, EEG speech decoding, or brain foundation models, reviewing paper quality, and generating structured Chinese/English summaries.

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。