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概要と使いどころ
Bright Data Web MCP gives MCP-compatible agents live web search, scraping, and optional browser-automation access through Bright Data’s web-access platform. It is built for agents that need current information, anti-bot resilience, and structured extraction without maintaining their own scraping stack.
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 browser-use to turn natural-language web tasks into repeatable browser automation backed by Playwright and agent loops. This skill helps an agent open sites, inspect page state, click, type, extract data, and recover from common UI changes with a real automation framework instead of brittle one-off scripts.
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。
Browser Use is an open source browser automation framework for AI agents that turns websites into controllable interfaces for multi-step tasks. It combines a Python SDK, browser orchestration, and model integrations so agents can navigate, extract data, and complete workflows in real browsers.
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。
Automates browser tasks with Browser Use, the open-source library that connects LLM reasoning to Playwright-driven web actions. Useful for navigating sites, filling forms, extracting structured page data, and running agentic browser workflows with screenshots and stateful 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。
Extracts structured citation data from academic repositories using BeautifulSoup4 with lxml parser. Parses DOI metadata, author affiliations, and reference lists from PubMed, arXiv, and Semantic Scholar HTML.
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。
Assess a public HTTP(S) page before building browser automation, extraction, or an integration. Use this skill to collect bounded structural evidence, readiness signals, risk flags, acceptance tests, and remediation priorities without sending credentials or accessing private targets.
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。
Streams audio from Twilio Media Streams over WebSocket to AssemblyAI real-time transcription, extracting speaker-diarized transcripts with word-level timestamps. Triggers entity detection and sentiment analysis via AssemblyAI LeMUR on completed call segments. Results are pushed to HubSpot or Salesforce contact records via their REST APIs.
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 event-driven architecture documentation from AsyncAPI 3.0 specifications. Uses the AsyncAPI parser-js library to extract channels, message schemas, and server bindings for Kafka and RabbitMQ.
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。
Transcribes audio and generates auto-chapters with summaries using AssemblyAI's /v2/transcript endpoint with auto_chapters=true. Extracts key topics, sentiment analysis, and content safety labels via AssemblyAI SDK.
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。
Give coding agents a design skill for greenfield UI, component work, audits, redesigns, and visual DNA extraction from screenshots or URLs.
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。
Apify SDK is the official JavaScript SDK for building Actors, crawlers, and data extraction workflows on Apify. It gives agents a structured way to run scraping jobs, store outputs, manage inputs, and combine crawler logic with browser automation when needed.
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。
Extracts structured text, metadata, and embedded objects from PDFs, Office documents, and 1000+ file formats using the Apache Tika REST API. Outputs clean Markdown or JSON with XMP metadata preservation.
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。
Study a merged or shipped tdmcp implementation and extract reusable learnings: code improvements, runtime/UX lessons, test gaps, docs updates, roadmap items, and harness changes. Use when the user asks to learn from a completed feature/project/PR/build, analyze what can be improved from an implementation, or turn a real installation experience into actionable tdmcp improvements. This is a post-implementation learning harness; it does not replace tdmcp-pipeline for building or tdmcp-quality-audit for broad repo audits.
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。
Comprehensive suite for processing YouTube videos. Use this when the user needs to: (1) Extract transcripts, (2) Generate visual infographics, (3) Create audio summaries (TTS) and videos, or (4) Perform full 'kitchen sink' processing of YouTube 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。
AI browser automation via CDP. Use when you need to control a browser, navigate pages, click elements, fill forms, extract content, or take screenshots.
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。
Credential operations: secret discovery, classification, extraction, conversion, offline cracking of hashes the operator already has as a credential job, policy-aware spraying, NetNTLM capture, generic SMB relay, and Windows/Linux harvest. Do not hijack an in-progress /ad-attack Kerberoast/AS-REP chain (that module cracks and uses the ticket itself). Do not DCSync, read LAPS LDAP, or escalate cloud IAM. Usable credentials are recorded; the operator chooses the next module.
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。
调用 Netgen 1.5.275 做 LVS 对比：综合网表 vs Magic 提取的 SPICE，必须 match 才能 signoff。触发场景：(1) bba-guru-pd extract 后做 LVS；(2) 显式 /bb-invoke-netgen。
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。
Clone un site web à l'identique à partir d'une URL : capture Playwright complète (screens full-page + fold par fold sur desktop/tablet/mobile, crops par section, états hover), extraction de tout ce que le navigateur expose (fonts, variables CSS, palette, typo, layout, breakpoints, animations, assets, console/network), reconstruction section par section, puis boucle de vérification par diff pixel et console propre. Utilise ce skill DÈS QUE l'utilisateur veut copier, cloner, répliquer, reproduire, « refaire pareil », s'inspirer fortement d'un site, d'une landing page, d'un template ou d'une page précise (« fais-moi la même chose que X », « copie ce site », « reproduis cette landing », « clone neverboring.ai », « je veux exactement ce design »), même s'il ne dit pas « clone ». Aussi pour auditer visuellement un site existant (screens complets, design tokens, fonts utilisées).
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。
Session lifecycle management. Parent skill for session-related skills: learning (pattern extraction) and compact (context compression).
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。
Extracts reusable patterns from sessions. Use at session end to capture debugging insights and project-specific knowledge.
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 says 'extract my brand voice', 'what is my writing style', or 'analyze my tone', or before any skill that writes copy for the site. Reads 5-10 published posts and persists tone, lexicon, sentence patterns, formality, signature phrases, and phrases the site never uses.
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。
Repurpose existing content into a native Threads post or thread. Take a LinkedIn post, X thread, blog, YouTube script, or newsletter and rewrite it for Threads: warm the tone, de-corporate it, refit to a short post or light thread, rebuild the hook to clear the soft fold, strip off-platform artifacts, run the humanizer, publish via Publora on approval. Not for writing from scratch (use threads-post-writer), auditing a draft (use threads-humanizer), or a hook teardown (use threads-hook-extractor).
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。
Reverse-engineer the hook from a viral Threads post or thread URL. Identifies which of the 10 canonical 2026 Threads formulas it uses (warm contrarian, data-point, build-in-public, quote-post, mini-list, relatable, listicle, story, curiosity-gap, how-I teardown), explains why it worked, and returns a blank template mapped to your topic with its primary goal (replies, reposts, likes, quotes). Use to learn from a post you admire. Not for writing your own (use threads-post-writer).
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。