「search skill」の検索結果

AI Berkshire skill: 未上市公司研究：多Agent并行深度研究框架. Source: skills/private-company-research.md.

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 publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

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 guide for writing systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides paragraph-level structural blueprints, writing patterns, venue-specific checklists, reviewer guidelines, LaTeX templates, and conference deadlines. Use this skill for all systems conference paper writing.

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。

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

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。

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

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。

Designs and implements production-grade RAG systems by chunking documents, generating embeddings, configuring vector stores, building hybrid search pipelines, applying reranking, and evaluating retrieval quality. Use when building RAG systems, vector databases, or knowledge-grounded AI applications requiring semantic search, document retrieval, context augmentation, similarity search, or embedding-based indexing.

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 this skill whenever a user specifically requests legal research or Westlaw Deep Research, asks for CoCounsel Legal or cocounsel legal support, or asks a question that requires explaining, analyzing, or synthesizing U.S. law.

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。

Convex is the backend agents get right on the first try: an all-TypeScript reactive platform where the database, server functions, scheduling, file storage, auth, and realtime sync are one type-safe system, every function is a transaction, and `tsc` catches most mistakes before deploy. Ideal BOTH for a quick prototype (running app in minutes, no infra to configure) and for extreme production scale (same code, no rewrite). Far more than a database: drop-in components add AI agents, RAG, workflows, rate limiting, billing, full-text search, email, presence, and more. Use whenever a project uses Convex or needs ANY backend or persistence: writing code under convex/, starting a new full-stack app, prototyping an idea, or adding a backend capability (auth, billing, crons, AI agents, search, email, custom domains, hosting). Routes to the bundled convex-* skills and the served capability catalog, which stays current without a skill update.

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。

Delegate tasks to OpenSpace — a full-stack autonomous worker for coding, DevOps, web research, and desktop automation, backed by an extensive MCP tool and skill library. Skills auto-improve through use, reducing token consumption over time. A cloud community lets agents share and collectively evolve reusable skills.

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。

Route broad or ambiguous life-sciences research requests to the right skills, normalize core entities, optionally parallelize independent evidence gathering with subagents when available, and synthesize a concise evidence-backed answer. Use when a user asks a general life-sciences question that could span multiple sources or analysis types.

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。

The protocol behind every investigation skill. Use when AI research must proceed without you: search-plan gate, Fact/Inference/Assumption labels, confidence stacking, diffable outputs.

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。

Research a company, industry, or competitor set using web search and seven analytical lenses. Use when you need structured intel that feeds downstream PM skills.

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。

Optimize for search engine visibility and ranking. Use when asked to "improve SEO", "optimize for search", "fix meta tags", "add structured data", "sitemap optimization", or "search engine optimization". Do NOT use for accessibility (use web-accessibility), performance (use core-web-vitals), or comprehensive site audits covering multiple areas (use web-quality-audit).

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。

Generative Engine Optimization (GEO) specialist — the technical, on-page publishing work that makes a given page or site discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines (Google AI Overviews, ChatGPT Search, Bing Copilot, Perplexity). Use when asked to 'optimize this page/site for GEO', 'optimize for AI search / answer engines', 'get my page cited by ChatGPT/Perplexity', 'improve AI visibility/citability', 'write an llms.txt', 'add citation-ready structure or schema for AI answers', 'otimizar para busca com IA', or to audit/create/improve a codebase for generative search. Do NOT use for AI-driven SEO content strategy or programmatic pages at scale (use ai-seo), classic keyword/SERP ranking (use seo), accessibility (use web-accessibility), or multi-area site audits (use web-quality-audit).

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。

When the user wants to build programmatic SEO with AI, create competitor alternative pages, optimize for AI Overviews, or scale content production. Also use when the user mentions 'SEO,' 'programmatic SEO,' 'AI content,' 'competitor alternative pages,' 'AI Overviews,' 'search optimization,' 'DataForSEO,' 'content at scale,' 'keyword strategy,' or 'organic traffic.' This skill covers AI-powered SEO strategy from keyword research through programmatic page generation. Do NOT use for technical implementation, code review, or software architecture.

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。

ERC-8004 Agent identity: 注册/更新/上架/下架/搜索agent, register/update/activate/deactivate/search — User/ASP/Evaluator(买家/卖家/评审员, 旧称仲裁者亦可); 我的agent/ASP, 找做X的ASP/agent有什么服务/endpoint怎么填/查口碑/传头像. + Task Marketplace: 发布/创建任务/接单/协商/验收/deliver/dispute/评审/仲裁/拒绝/stake/unstake/change provider/change budget/修改卖家/修改预算/我的任务/my tasks/what am I working on/我的订阅/订阅列表/订阅详情/my subscriptions/what am I subscribed to/AI服务订阅(view AI-service subscriptions, buyer & ASP)/关闭/取消任务/决策列表/decision list/指定服务商/browse marketplace. + task watch: 监听任务进展/历史消息/未读消息/未决策/outstanding decisions. + device routing: 设备列表/我登录了哪些设备/device list, 本设备或指定设备订阅消息开关. + okx-a2a missing/uninitialized. Match by meaning. MUST ACTIVATE on inbound envelopes: (1) {agentId, message:{source:"system", event, jobId,...}} system event; (2) {msgType:"a2a-agent-chat", jobId, sender:{role},...} agent-to-agent task chat (sender.role = COUNTERPARTY, not you); (3) literal "Read the okx-ai skill" (or legacy "Read the okx-agent-task skill") in the envelope.

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。

Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, organizing workflows into folders, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides tool selection guidance, parameter formats, and common patterns. IMPORTANT — Always consult this skill before calling any n8n-mcp tool — it prevents common mistakes like wrong nodeType formats, incorrect parameter structures, and inefficient tool usage. If the user mentions n8n, workflows, nodes, or automation and you have n8n MCP tools available, use this skill first.

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 LoopX worker is operating an auto-research lane, demo pane, frontier item, evidence packet, promotion/retirement decision, or visible tmux/Codex auto-research rehearsal. Identity must come from the LoopX role profile and quota/frontier packet; this skill only provides role-specific execution checklists, artifact contracts, and stop conditions.

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-powered web research assistant that leverages BrowserAct API to supplement restricted web access by searching the internet for additional information. Designed for OpenClaw and Claude 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。

Extract complete product information from any e-commerce product page. Returns name, price, currency, brand, images, description, SKU/ASIN/EAN/UPC/GTIN/MPN identifiers, stock availability, rating, review count, variants, and seller. Works on Shopify, Amazon, WooCommerce, eBay, Walmart, Etsy, AliExpress, Alibaba, Target, Best Buy, Rakuten, Magento, BigCommerce, PrestaShop, and any public e-commerce site. Accepts product URL, keyword, or product identifier (SKU/ASIN/EAN/UPC). Use when: scrape product page, get product details, extract price and availability, product info extraction, check product data, product detail scraping, get product from URL, keyword product search, ASIN lookup, EAN search, UPC lookup, price check, product research, compare products, monitor product price, get product images, product brand and description, ecommerce data extraction, product catalog scraping, product page scraper, get item price, fetch product info.

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。

Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and follower count across X, Instagram, Facebook, LinkedIn, TikTok, YouTube, Pinterest, Reddit, Snapchat, Threads, and more. Use when user wants to find someone's social media accounts, look up social profiles, discover where a person is active online, find brand social media pages, search social accounts by name, track digital footprint, find influencer profiles, check a company's social presence, locate a public figure's profiles, social media lookup, social media finder, find accounts across platforms, social profile search, online presence discovery, who is this person on social media, what social media does X use, find username across platforms.

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。

eBay sold-listings scraper across 8 marketplaces (ebay.com/.co.uk/.de/.fr/.it/.es/.ca/.com.au). Takes keyword plus filters (category, price range, item condition, item location, sort order, completed toggle) and returns paginated real-sale records with itemId, url, title, condition, conditionId, endedAt, soldPrice, soldCurrency, listingType (best_offer_accepted / buy_it_now / auction), isBestOfferAccepted, buyingFormat, bidCount, shipping, totalPrice, thumbnails, seller info, sellerType. Use when user mentions ebay sold, ebay sold listings, ebay sold prices, ebay completed listings, ebay comps, ebay resale prices, ebay auction sold results, ebay best offer accepted, scrape ebay sold, ebay market research, ebay pricing intelligence, ebay flipping research, real sold prices ebay, get sold prices from ebay. Also applies to price benchmarking, sold-price analytics, resale valuation, cross-marketplace price arbitrage, appraisal for collectibles, brand demand tracking on ebay.

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。

Discover and install agent skills from the open ecosystem. Use when you encounter an unfamiliar domain, framework, or workflow that you lack specialized knowledge about, or when your coordinator suggests searching for skills before starting a 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。

Use when another PPT Skill needs web search, image search or download, or image generation and the host Agent's equivalent native capability is absent or has failed.

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。