「search skill」の検索結果

MUST USE when the user needs current, online, or web-derived information — news, latest releases, vendor docs, real-world examples, recent changes, or anything not in the model's training set. LLM-neutral skill that exposes a unified web search CLI behind a single command. Runs single or multi-provider in parallel, saves raw + normalized JSON to a temp directory, prints the path so callers can pipe through rg / jq / grep. Zero-config out of the box. Works identically on macOS, Linux, WSL, Git Bash for Windows, and any environment with Python 3.8+. Triggers: 'search the web', 'look up online', 'google this', 'find current information', 'latest news', 'recent docs', 'check the internet', 'web search', 'browser search', 'research this', 'what is the latest', 'who is X', 'find examples of', 'is there documentation for', 'how do people solve', 'web-search', 'web_search'.

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Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB 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。

Search the public web and crawl URLs via the Unique AI Platform's `unique-cli web-search` command, with automatic per-turn citation tracking so cited web facts render as clickable external reference chips and `<sup>N</sup>` footnotes on the Unique platform. ALWAYS use this skill when the user asks to search the public web, research a topic online, look up news/articles/regulations, fetch the contents of one or more URLs, or perform any "two-phase" web research (search → review snippets → crawl selected URLs for full content). Routes through the Unique AI Platform's `/web-search-api` endpoints, so the engine (Google, Brave, Tavily, Jina, Firecrawl, …) and crawler are resolved server-side from the current environment — you never need to manage engine API keys yourself. Use this instead of fabricating answers from training data whenever fresh / source-cited information is needed. Do NOT use this skill for the internal knowledge base (`unique-cli search`) or for arbitrary tool execution (`unique-cli mcp`).

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 actionable skill knowledge from academic papers and research articles, assess credibility, run security checks, and either improve existing skills or create new ones. Load when the user asks to learn from a paper, extract insights from a research paper, turn a paper into a skill, apply paper findings to skills, read this paper and improve my skills, or process a research article. Also triggers on "skill from paper", "learn from this paper", "paper to skill", "extract from this research", "apply this paper", or when the user uploads or links to an academic PDF or paper 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。

Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.

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。

ClawHubで目的に合うプラグインやスキルを探し、スキルの検証・導入・更新・削除から公開・同期まで、OpenClawと専用CLIで扱うスキル。

• 必要な機能を持つプラグインを探したいとき
• 指定したスキルを検証して導入したいとき
• 導入済みスキルを更新・削除したいとき

Search Xiaohongshu (RedNote / xhs) notes by keyword and return a paginated list with title, author, engagement stats (likes, collects, comments), cover image URL, and xsecToken for detail lookup. Use when user mentions find notes on xiaohongshu, search rednote, search xhs, scrape xiaohongshu search, xiaohongshu keyword search, rednote post search, xhs search results, monitor xiaohongshu topics, KOL content discovery via xiaohongshu, xiaohongshu note list, rednote scrape, xhs data collection, collect xiaohongshu posts, xiaohongshu topic search, xiaohongshu content monitoring, rednote post list, xhs keyword scrape.

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。

This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search results.

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 Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.

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 product list from any e-commerce category page, search results page, or keyword search with filters. Returns paginated product arrays with URL, name, price, currency, image, rating, review count per item. Supports URL input, keyword search, and site-scoped search with filters: price range, brand, category, minimum rating, in-stock only, and sort order. Works on Amazon, eBay, Walmart, Shopify collections, WooCommerce shops, Google Shopping, and any public product listing page. Use when: category listing, product search results, ecommerce search, search for products, filter products by price, list products from a site, price range filter, brand filter, keyword search with filters, scrape product list, product catalog extraction, get all products from category, bulk product URLs, product list scraping, category page scraper, search results scraper, multi-page product extraction.

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。

This skill should be used when the user asks to "brainstorm research ideas", "use 5W1H framework", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", or mentions research project initiation phase. Provides comprehensive guidance for research startup workflow from idea generation to planning.

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。

一键启用 SenseNova-Skills-DeepResearch，用于行业与市场研究、竞品分析、政策或技术调研、商业尽调、趋势分析、方案对比、事实核查，以及研究报告、白皮书等交付场景。用户提出深度研究、调研、调查、尽调、research/deepresearch，或任务需要跨来源取证、多维度比较和交叉验证时主动使用；Skill 会完成环境检查、SenseNova-Skills-DeepResearch 安装或升级、Harness 与 Search/Camofox 准备、参数确认、研究启动和 Web 进度提示。简单常识问答、单一来源整理和纯文字润色不使用。

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。

This skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.

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。

Start a new research project by conducting a structured interview to formalize a research idea, then generates research questions with identification strategies and a project spec. Make sure to use this skill whenever the user wants to develop or document a new research idea — not to search for literature or data. Triggers include: "new project", "start research", "I have an idea", "help me develop this", "I want to study X", "help me formalize this idea", "what's my research question", "what identification strategy should I use", "write up my project idea", or when the user describes a topic they want to turn into a 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。

This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.

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Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research 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。

When the user wants to analyze Google Search Console data, use the GSC API, or interpret search performance. Also use when the user mentions "GSC," "Search Console," "indexing report," "Core Web Vitals," "Enhancements," "Insights report," "search performance," "search queries," "search performance report," "URL inspection," "impressions," "CTR," "average position," "index coverage," "GSC data analysis," "Search Console API," or "searchanalytics.query." When the user wants to rewrite title tags (not only report on them), use title-tag. For meta description rewrites, use meta-description.

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 keyword research, classify by search intent, cluster into topical groups, and prioritize for content production. Use this skill whenever the user asks to do keyword research, find target keywords, identify ranking opportunities, classify search intent, build a topical map, or plan a content strategy around what people search for. Triggers on keyword research, keyword strategy, search intent, keyword clustering, topic clusters, keyword difficulty, search volume, ranking opportunity, content gap, what should I write about, target keyword, primary keyword, secondary keyword, long-tail. Also triggers when planning a content calendar or new site without keywords yet defined.

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Implements HIPAA Privacy Rule requirements for research uses of protected health information under 45 CFR §164.512(i). Covers IRB and Privacy Board waivers of authorization, individual authorization for research, limited data set and data use agreements, preparatory to research provisions, and decedent research provisions. Keywords: HIPAA research, IRB waiver, Privacy Board, authorization, limited data set, preparatory research, de-identification, Common Rule.

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。

Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, semantic or structural nearest-neighbor lookup, or hybrid search (vector + fulltext, multiple vector sources, or graph-derived scores). Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext-only/keyword-only search — use neo4j-cypher-skill. Does NOT compute GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.

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。

Search the agent skills ecosystem to discover and install skills that extend AI coding agent capabilities. Use when user asks "how do I do X" (X being a common task), "find a skill for X", "is there a skill that can...", or expresses interest in extending agent capabilities. Triggers on "find a skill", "install a skill", "skill for [task]", "can you do X", "I need help with [domain]", "how do I [task]". Do NOT use when user has explicitly asked to proceed without a skill, or when the task is better handled by agent's built-in capabilities (file operations, git, basic coding).

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。

Perform visual similarity search for utility model patents using an image URL, with filtering by country, legal status, date ranges, and assignee. Supports utility model patents only (type U) with shape-only or shape+pattern+color matching models. Triggered when users mention utility patent image search, utility model patent search, utility patent infringement check, product structure patent search, or utility model visual search. Even if the user does not explicitly mention "utility patent," this skill should be triggered whenever the need involves searching for similar utility model patents through an image. For design patents, use ecommerce.Nexscope-patent-image-search instead.

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。

Nexscope Ozon keyword reverse lookup: reverse-looks up Ozon (and Wildberries) search keywords by a list of product SKUs (up to 20), returning which search terms those products appear under (organic/ad search terms), with multi-dimensional filtering by search volume, growth, product count, seller count, competitor count, natural rank, ad rank, exposure, conversion, cart-add conversion, etc. Each keyword carries monthly search volume, growth, market space, competitor/seller counts, average price, cart-add conversion, top products, and organic/ad channel, rank, exposure, and conversion (dimension) market profiles. Use for Ozon keyword reverse lookup, listing keyword optimization, competitor traffic word mining, and ad keyword analysis. Trigger when the user mentions Ozon keyword reverse lookup, Ozon reverse keyword search, Ozon SKU keyword reverse, Ozon product traffic keywords, Ozon competitor ranking keywords, Ozon organic/ad keyword reverse lookup, Nexscope Ozon, Ozon keyword back search, Ozon reverse keyword lookup, Ozon SKU keyword reverse. Also trigger when the intent is to reverse-lookup Ozon search keywords by product SKU and view market profiles, even without explicitly mentioning Nexscope.

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Multi-dimensional Amazon product search and filtering based on Nexscope data, covering 14 marketplaces, with support for historical monthly snapshot lookback. Trigger when the user mentions Nexscope product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot review, product search, monthly sales/revenue, ABA keyword product discovery, price range filtering, new product discovery, multi-condition combined filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot. Even if the user does not explicitly mention "Nexscope", if their need involves Amazon product search, filtering, comparison, or product exploration by category/brand/seller dimensions, this skill should also be triggered.

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。