「search skill」の検索結果

Installs, diagnoses, repairs, and personalizes the official Tencent IMA skill (a wrapper around upstream ima-skill, not a replacement), including fan-out search across IMA knowledge bases with priority boosting. Use when the user mentions IMA / 腾讯 IMA / ima-skill, needs IMA API key setup, 知识库搜索 / 笔记搜索, imports URLs into a KB to extract content, or hits "Skipped loading skill(s) due to invalid SKILL.md" (ima-skill's missing-YAML-frontmatter bug).

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 a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with `skillpack.json`, local skills under `skills/`, starter prompts, start scripts, and an optional zip package.

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 "search for papers", "find research papers", "search arXiv", "search PubMed", "look up a DOI", "download a paper", "search IEEE", or "search Scopus".

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。

Deep research and discovery before building something new. Explores local projects for reusable code, researches competitors, reads forums and reviews, analyses plugin ecosystems, investigates technical options, and produces a comprehensive research brief. Three depths: focused (30 min), wide (1-2 hours), deep (3-6 hours). Triggers: 'research this', 'discovery', 'explore the space', 'what should I build', 'competitive analysis', 'before I start building', 'research before coding'. Not for cited fact-checking research reports (a separate harness does those); this is pre-build product discovery.

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 upstream brand discovery covering audience research, competitive landscape, category dynamics, problem space, and positioning territory exploration. Use this skill at the very start of a brand or website project when the user needs to understand who they're for, who they compete with, what the audience actually needs, and where the brand could plausibly stand. Triggers on brand discovery, audience research, market research, competitive scan, category research, customer research, who is this for, who are we, positioning research, intake, kickoff. Also triggers when a creative brief is requested but the upstream inputs (audience, competitors, problem space) are not yet clear.

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 US employment law topic across federal, state, and city jurisdictions and produce structured research notes with proper source attribution. Use this skill any time the user asks about US employment laws, regulations, or pending legislation - from a single jurisdiction question to a 50-state survey. Triggers include phrases like "research [employment law topic]", "what are the laws on [employment topic]", "state-by-state [employment topic]", "help me understand [topic] across the US", or any prompt that asks for a legal landscape overview before another deliverable. Always run this BEFORE the employment-law-dashboard skill if a dashboard is the eventual output. Output is a structured research note that distinguishes primary sources (statutes, regs, agency guidance) from secondary sources (law firm alerts, tracker orgs).

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。

Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.

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。

Pull Google Search Console data and perform search performance analysis. Use when asked about search rankings, clicks, impressions, CTR, index coverage, Core Web Vitals, or sitemap status. Trigger phrases: "search console", "GSC", "search performance", "clicks and impressions", "CTR analysis", "index coverage", "core web vitals", "URL inspection", "sitemap status", "ranking data", "search queries", "keyword positions".

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。

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

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 invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.

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。

Deep web research skill using parallel subagents + chromux browser-explorer + Gemini. Spawns multiple WebSearch research agents AND browser-explorer agents (via chromux for JS-heavy/dynamic sites), plus a Gemini CLI deep research source, then synthesizes everything into a cited report. Uses WebSearch, WebFetch, chromux browser-explorer, and Gemini CLI. Invoke with /deep-research <topic>.

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。

Algolia Search Integration workflow skill. Use this skill when the user needs Expert patterns for Algolia search implementation, indexing and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Builds a portable, embedding-free knowledgebase from a set of files and delivers it as a self-contained `.skill` bundle (BM25 index + bundled searcher + query protocol). Use when a user wants to turn uploaded files, a folder, or a corpus into a searchable knowledgebase they can hand to any agent — phrased as "make a knowledgebase", "build a KB skill", "package these docs for retrieval", "create a searchable bundle", or references to a `.skill` KB. The output runs anywhere with Node or Python — no model, no install, no network. Distinct from `bm25` (ephemeral in-session search) and `building-github-index` (markdown project-knowledge index).

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 GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.22.0+). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever, ToolsRetriever), external vector DB retrievers (Weaviate, Pinecone, Qdrant), retrieval_query Cypher fragments, query_params, filters, GraphRAG pipeline wiring (GraphRAG + LLM + prompt), all LLM providers (OpenAI, Anthropic, Gemini/VertexAI, Bedrock, Cohere, Mistral, Ollama), embedder setup, index creation, token usage tracking, Cypher 25 SEARCH clause, and LangChain/LlamaIndex integration. Does NOT handle KG construction — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-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 and filter TikTok global e-commerce products based on FastMoss data, supporting keyword search, multi-dimensional filtering (category, shop type, commission rate, sales, creator count, etc.) and sorting. Trigger when users mention TikTok product selection, TikTok product search, TikTok product data, TikTok creator sales, TikTok commission rate, TikTok bestseller tracking, TikTok GMV analysis, TikTok product search, TikTok product research, TikTok creator sales, TikTok commission rate, TikTok GMV analysis, FastMoss. Even if the user does not explicitly mention "FastMoss", trigger this skill whenever their need involves searching product data or analyzing product performance on TikTok.

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 market hot keyword search: filters Ozon (and Wildberries) market keywords by multi-dimensional metrics including search volume, growth, product count, seller count, competitor count, price, sales, conversion concentration, etc. Each keyword carries monthly search volume, growth, market space, competitor/seller counts, average price, cart-add conversion, top products, and market profile. Use for Ozon keyword selection, blue-ocean keyword mining, and market opportunity analysis. Trigger when the user mentions Ozon hot keywords, Ozon keyword market analysis, Ozon keyword selection, Ozon blue-ocean keywords, Ozon search volume, Wildberries keywords, Nexscope Ozon, Ozon market keyword search, Ozon keyword research, blue ocean keywords Ozon. Also trigger when the intent is to filter Ozon market keywords by metrics and view market profiles, even without explicitly mentioning Nexscope.

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 Russia product search and reverse lookup. Searches Ozon products in the Nexscope database by Russian keyword or SKU, returning product ID, title, brand, and seller information. The entry point for Ozon product discovery and competitor analysis chains. Trigger when the user mentions Ozon product selection, Ozon product search, Russian e-commerce product selection, Ozon keyword search, Ozon SKU query, Nexscope Ozon, Ozon product search, Nexscope Ozon, Russian marketplace, Ozon SKU lookup, Ozon keyword search. Also trigger when the intent is to discover or reverse-lookup products on Ozon Russia by keyword or SKU, even without explicitly mentioning Nexscope.

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 Overview (AI Mode) scraping via Google Search. Returns AI-summarized key points for a single keyword, ideal for deep research, technical Q&A, long-tail product selection, and cross-border consumer preference analysis using the latest web information. Single-round only; follow-ups require the agent to summarize context and issue a new request. Triggered by: Google AI, AI Overview, AI Mode, Google AI search, AI search, deep research, consumer preference analysis, web summary, long-tail product research, cross-border market insights.

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 and analyze Amazon ABA (Brand Analytics) search term data, covering 15 marketplaces with nearly 3 years of weekly data. Trigger when the user mentions ABA data, Amazon search term analysis, keyword mining, search ranking trends, market opportunity analysis, seasonal keywords, high-click low-conversion analysis, blue ocean keyword discovery, competitor keyword analysis, ABA data, search term report, keyword mining, search ranking trends, blue ocean keywords, click share, conversion share, seasonal keywords, market opportunity analysis, competitor keywords. Even if the user does not explicitly mention "ABA", if their need involves Amazon search term data and ranking analysis, 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。

Advanced Amazon product search and filtering powered by Nexscope data, supporting multi-dimensional criteria including category, price, monthly sales, keywords, BSR rank, review count, rating, package dimensions, weight, fulfillment type, and more. Trigger when users mention Nexscope product selection, Amazon product search, advanced product selection, BSR filtering, sales rank filtering, keyword-based product discovery, category search, competitor screening, niche product discovery, historical rank filtering, or similar terms. Even if the user does not explicitly mention "Nexscope," trigger this skill whenever the request involves multi-criteria Amazon product search, sales-metric-based filtering, or advanced product selection beyond simple keyword search.

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 and discovers academic papers across multiple sources (Semantic Scholar, arXiv, Tavily, Exa, Gemini deep research, AMiner, Google Scholar) with adaptive engine selection based on query type. Returns ranked, deduplicated results with metadata (authors, venue, year, citations, abstract, PDF link). Use when the user asks to find papers / literature / publications / preprints / references on a topic, search for related work, look up a specific paper by title or DOI or arXiv ID, find papers by an author, find recent SOTA / state-of-the-art work, survey a research area, or run a deep / comprehensive literature search with synthesis.

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。

Synthesis step in the multi-angle technical research pipeline. Receives structured outputs from all four research angles (api-state, ecosystem-research, impact-measurement, codebase-auditor), applies cross-angle signal weighting and conflict resolution, and produces a single synthesized Research section. Invoked by the technical-researcher orchestrator after all angle skills complete. Returns content to the orchestrator — does not write to the backlog.

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-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web 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。

Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.

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。