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概要と使いどころ
browser-use is an open-source Python framework for letting AI agents interact with websites through a real browser. It supports local execution, optional cloud browsers, custom tools, and a CLI for persistent browser sessions.
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。
Manage and tag music libraries with beets, the Python-based CLI tool that auto-tags audio files using MusicBrainz metadata. Import, organize, deduplicate, and query your music collection with a powerful plugin system and flexible query language.
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。
Generates Blender Python (bpy) scripts that programmatically create Geometry Nodes modifier trees, using the node_groups API and GeometryNodeTree interface for parametric 3D asset generation.
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。
Lets agents operate Google NotebookLM/Gemini Notebook through a Python API, CLI, skill, MCP server, or REST server to create notebooks, add sources, ask cited questions, generate artifacts, and download exports.
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。
Extract structured intelligence from audio using the AssemblyAI API with sentiment analysis, entity detection, topic modeling, and auto-chapter generation. Uses the assemblyai Python SDK for transcript processing 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。
Query Chinese A-share, ETF, index, financial statement, valuation, capital-flow, and technical-indicator data through the AShareHub Python SDK and hosted API. Use this skill when an agent needs structured China market data as pandas DataFrames.
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。
Separates audio tracks into individual stems (vocals, drums, bass, other) using Meta's Demucs neural network model via the demucs Python package. Supports batch processing of WAV and MP3 files, outputs isolated stems in FLAC or WAV format, and integrates with FFmpeg for format conversion and loudness matching post-separation.
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 Retentioneering's Python toolkit, MCP server, and agent skills to run reproducible customer-journey and event-log analytics that agents can validate and cross-check.
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。
Validates Ansible playbooks in check mode using ansible-playbook --check --diff and the Ansible Python API. Detects idempotency issues, undefined variables, and unreachable hosts before production runs.
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。
Apprise is a Python library and CLI that sends push notifications to over 100 services including Telegram, Discord, Slack, Amazon SNS, Gotify, email, and more through a single unified API. It supports attachments, images, and asynchronous delivery.
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。
Executes Ansible playbooks for server diagnostics and remediation using ansible-runner Python SDK. Supports inventory parsing, vault-encrypted credentials, and real-time task output streaming.
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。
AgentQL is TinyFish's web automation and extraction toolkit that layers a natural-language query system on top of live sites. Its Python and JavaScript SDKs integrate with Playwright and let agents target data and interface elements without depending on brittle CSS selectors alone.
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。
Agno is a high-performance Python framework for building, running, and managing agentic software at scale. It provides a three-layer architecture — framework, runtime, and control plane — enabling developers to go from agent prototype to production API in roughly 20 lines of code.
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。
Design a tdmcp feature into an implementable spec before any code is written — choose the layer, define the Zod input schema, lay out the TD network topology, plan the bridge/Python approach, sketch a UI wireframe when relevant, and list probe-first risks + the test plan. Use whenever a tdmcp feature idea needs a design/wireframe/spec, or when someone asks to plan/scope/architect a new tool, generator, effect, control, or AI prompt for the TouchDesigner MCP server.
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 the octop-browser Python package: cut a release branch from develop, bump version, update CHANGELOG / README, open a PR to main; after merge, Actions tag on main (PyPI + GitHub Release) and sync main into develop. Use when the user asks to publish, release, bump version, cut a release, or run /publish.
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。
当用户需要将生产 Skill 安装或更新到系统级目录，或需要创建、检查、更新统一的 benszapi Conda 运行环境与其中的 BSK 等托管 Python 工具时使用。默认处理 alpha；只有用户明确指定时才处理 beta；支持 72 小时 TTL 到期后的静默增量更新。
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。
后端开发专家。精通 Node.js/Python/Go/Rust 等后端技术栈，专注于 API 设计、数据库优化、认证授权、微服务架构和性能调优。用于后端服务开发、API 设计和系统架构。
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。
Knit/render R Markdown (.Rmd) to HTML reliably in this repo (auto-bootstrap pandoc, set correct knit_root_dir, and run rmarkdown::render via a Python wrapper).
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 scraping JavaScript-heavy pages or SPAs, crawling multiple URLs concurrently, extracting structured data with reusable CSS/JSON schemas, or building automated web data pipelines. Wraps the Crawl4AI library (`crwl` CLI and Python SDK) with schema-generation patterns for LLM-free extraction. Triggers on crawl4ai, crwl, scrape JS-heavy site, scrape SPA, headless browser scrape, schema-based extraction, batch crawl, sitemap crawl, web data pipeline. SKIP when a static HTML page can be read with `defuddle` / `fetch-web` — those are faster cold-start and don't need a 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 the user wants Codex to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Codex without changing the generated Python harness format.
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 maintain modern WordPress plugins and MCP servers, including hybrid WordPress+MCP products. Use when implementing plugin architecture (PHP, REST API, Gutenberg/admin/page-builder integrations), MCP tooling (TypeScript/Python, stdio/HTTP transport), security hardening, licensing/updates, and delivery workflows from scaffold to distribution.
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。
Hot-reload a Python function implementation from the latest file content without restarting the process. Use this to apply code fixes live after identifying a bug with watch/trace.
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。
Trace execution time of Python method invocations in a live process with call stack visualization. Use this to see a hierarchical call tree showing which sub-calls are slow and where time is spent within a function.
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。
Inspect stack frames of a running Python process including thread stacks, native C-level frames, and async coroutine stacks. Use this to see what each thread is currently doing and diagnose hangs, deadlocks, or stuck async tasks.
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。