385건 · 관련도순
Search WeChat articles by keyword and retrieve full text alongside titles, authors, publication dates, article links and cover image URLs. Set collection limits and publication date filters to gather material for topic, brand or competitor research.
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Automate Chatfai operations through Rube MCP, a connection to external tools. The skill searches Composio’s toolkit for available actions, checks required inputs and authentication status, and executes the selected operations.
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Automate Chatfai operations through Rube MCP, a connection to external tools. The skill searches Composio’s toolkit for available actions, checks required inputs and authentication status, and executes the selected operations.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Automate Chatwork operations through Rube MCP, a connection for agent tools. The skill discovers available actions and their current input requirements, checks the service connection, and executes the tools returned by the search.
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Support decisions with market, technical, competitor, and other research. Draft prompts for external research tools, condense existing reports into source-cited summaries, or conduct web research directly, including comparisons between candidates.
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Automate Chatwork operations through Rube MCP, a connection for agent tools. The skill discovers available actions and their current input requirements, checks the service connection, and executes the tools returned by the search.
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Research uncertain design choices, algorithms, or API usage through approved web searches or optional ChatGPT consultation. Get concise options with sources, with separate approval required before sending text externally and before implementing a chosen approach.
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Automate supported 2chat tasks through Rube MCP and Composio. The skill finds available tools, checks the service connection, and uses current input requirements to carry out the requested operations.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Automate supported 2chat tasks through Rube MCP and Composio. The skill finds available tools, checks the service connection, and uses current input requirements to carry out the requested operations.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Automate supported Chatbotkit tasks through Rube MCP and Composio. Discover the available operations and required inputs, check the connection, and execute tasks with the current tool specifications rather than relying on fixed arguments.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Automate supported Chatbotkit tasks through Rube MCP and Composio. Discover the available operations and required inputs, check the connection, and execute tasks with the current tool specifications rather than relying on fixed arguments.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Research a topic to support a decision, three ways: draft a research prompt for the user to run in their own tool (ChatGPT, Gemini, Grok, Perplexity, …), turn a finished research report into a short summary with cited sources that other skills can use directly, or run the research here with parallel web searches. Built-in research types: market, domain, technical, competitive, user-voice, academic-lit; also supports choosing between candidates, and custom types via overrides. Use when the user says "deep recon", "research this", "draft a research prompt", "process this research report", "market research", "domain research", "technical research", "competitor research", "literature review", or "help me choose between"
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Find past discussions across existing screenpipe, Codex, Claude, Cursor, and Gemini CLI chats by title, workspace, or message text. With explicit authorization, send follow-up work to a specific supported chat; Gemini CLI supports search only.
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Get guidance on Codex, OpenAI APIs, and ChatGPT Work using official documentation with citations. Use it to investigate settings and errors, compare models, plan migrations, or work on prompts and API integrations.
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Assess a website separately for five AI search services, including ChatGPT and Google AI Overviews. Compare scores, identify gaps in content and platform presence, and receive actions organized by priority and timeframe.
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Create, audit, and improve pages for AI search engines by checking crawl access, metadata, clear answers, sources, and structured data that describes page content. It produces prioritized fixes and citation-friendly pages without guaranteeing inclusion in AI answers.
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Analyze actual GA4 visits from AI services such as ChatGPT and Perplexity. Compare traffic trends, landing pages, and conversions, then identify page patterns and specific content changes that may improve visibility in AI search.
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Submit shopping questions to Amazon's Alexa/Rufus assistant and collect answers as JSON, a structured data format. Use product search results as context for category research, or run a series of general shopping questions.
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SEO, AEO (Answer Engine Optimization), and GEO strategy for search engines and AI visibility. Use when working on "SEO audit," "technical SEO," "on-page SEO," "AI search optimization," "AEO," "GEO," "AI visibility," "optimize for ChatGPT," "optimize for Perplexity," "AI Overviews," "answer engine optimization," "generative engine optimization," "AI citations," "featured snippets," "meta tags," "schema markup," "search ranking," "content optimization," "E-E-A-T," "structured data," "search console," "SEO health check," "why am I not ranking," "AI search readiness," "backlink strategy," "link building," "domain authority," "programmatic SEO," "SEO at scale," "template-based SEO," "AEO monitoring," "AI search monitoring," "JSON-LD," "rich snippets," "schema.org," "SERP analysis," "search intent," "site architecture," "information architecture," "URL structure," "internal linking," or "navigation." For keyword research, see keyword-research-and-clustering.
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End-to-end research workflow skill for investment analysts and policy researchers. Three scope modes the user picks at trigger time — light (4-5 page decision memo, ~15 min, 0 charts), medium (12-15 page topic brief, ~1 h, 6-10 charts), heavy (flagship report 30-40 pages / 15k+ words, ~2-3 h, 25-35+ charts, multi-stage workflow, multi-LLM, PDF + Word + WeChat + HTML derivations). Reports default to English; the AI replies in the user's chat language. Battle-tested on real macro/policy/equity reports (e.g. Saudi Vision 2030 deep-dive). Triggers when user types /analyst-research, /flagship-research, or describes needs like "research report", "topic analysis", "investment research", "做研报", "投研报告", "主题分析", "深度分析", "policy assessment", "industry deep-dive". Not for: pure news commentary (use topic-brief), slide decks (use deckster-slide-generator), one-shot Q&A.
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Work with the @upstash/redis TypeScript/JavaScript SDK, a serverless HTTP-based Redis client for Next.js, Vercel, Cloudflare Workers, edge runtimes, and Node.js. Use when adding a cache (cache-aside, write-through, TTL and expiration strategies), session storage and user sessions, a key-value store, leaderboards and rankings with sorted sets, counters, distributed locks, queues with lists, streams and consumer groups, sparse index-addressed arrays and ring buffers (ARSET, ARINSERT, ARRING, ARGREP, AROP), embeddings and nearest-neighbour vector search stored inside Redis (VECTOR commands via redis.vector, separate from @upstash/vector), JSON documents, pipelines and MULTI/EXEC transactions, Lua scripting, read replicas, or full-text search, typo-tolerant search, facets, aggregations, and search over Redis stream entries with Upstash Redis Search (different from regular FT.SEARCH; also available for TCP clients via @upstash/search-redis and @upstash/search-ioredis). Also use when migrating from ioredis or node-redis, when a Redis connection is needed from a serverless function without connection pooling, when integrating @upstash/ratelimit, or when the user says Redis cache, KV store, session store, serverless Redis, or Upstash Redis. Also use when building AI agents on Redis with Upstash AgentKit (agent memory, chat history, RAG tools, tool caching, chat persistence, resumable streams, distributed locks) for the Vercel AI SDK, TanStack AI, or Vercel Eve. Supports automatic serialization/deserialization of JavaScript types.
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Search inside past agent sessions and continue the one that matters with a single command. Uses a separate episodic session index, so raw chat noise never pollutes the curated RAG. Triggers: "/chat-search", "which chat discussed X", "did we already research X", "search old chats".
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Audit how a brand appears in AI search answers and identify improvements to its content and website access. Review citation patterns, clear answer structure, supporting evidence, and whether AI systems can retrieve key information.
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