Structured framework for planning product launches, feature announcements, and go-to-market strategies. Organizes launches across five phases (internal, alpha, beta, early access, full) with specific actions and goals for each stage Uses the ORB framework to balance owned channels (email, blog, community), rented channels (social, app stores), and borrowed channels (guest posts, influencers, partnerships) Includes dedicated Product Hunt strategy with pre-launch preparation, launch-day tactics, and post-launch conversion guidance Provides launch checklist covering pre-launch setup, launch-day coordination, and post-launch user education and retention Emphasizes treating launches as ongoing moments rather than one-time events, with guidance on spacing feature announcements and maintaining momentum
SEO-optimized competitor comparison and alternative pages that position your product against rivals. Covers four page formats: singular alternatives, plural alternatives, you vs. competitor, and competitor vs. competitor comparisons Includes centralized competitor data architecture for consistent, maintainable information across all comparison pages Provides structured research process covering product features, pricing, reviews, and customer feedback with quarterly update cadence Emphasizes honest positioning that acknowledges competitor strengths and clearly defines who each product serves best
Web search with optional full-page content extraction from results. Returns real search results as JSON with optional --scrape flag to fetch complete page markdown for each result, avoiding redundant fetches Supports filtering by source type (web, images, news), category (GitHub, research, PDF), time range (past hour/day/week/month/year), location, and country Use --limit to control result count and --scrape-formats to customize output formats when extracting full content Part of a workflow escalation pattern: search first to discover URLs, then use dedicated scrape/map/crawl skills for deeper extraction
Bulk extract content from entire websites or site sections with depth and path filtering. Crawls pages following links up to configurable depth limits and page counts, with path inclusion/exclusion filters to scope extraction Supports async job polling or synchronous waiting with progress display via --wait and --progress flags Offers concurrency control, request delays, and JSON output formatting for integration into agent workflows Part of a four-step escalation pattern: search → scrape → map → crawl, used when single-page extraction is insufficient
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers,"…
Integrate Firecrawl `/search` into product code and agent workflows. Use when an app needs discovery before extraction, when the feature starts with a query…
Install the byted-web-search skill for your AI agent. Published on skills.volces.com.
When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,'…
Web search with LLM-optimized results, content snippets, and relevance scores. Supports four search depths (ultra-fast, fast, basic, advanced) with configurable result counts up to 20, plus domain filtering and time-range constraints Returns structured JSON output with content snippets, relevance scores, and metadata optimized for LLM consumption Includes specialized search modes for news and finance topics, with optional AI-generated answers and full page content extraction Integrates into multi-step research workflows: search → extract → map → crawl → research
Fetch your next meeting's agenda, attendees, and linked documents from Google Calendar. Retrieves the upcoming event with full attendee list and description details Supports multiple calendar selection via --calendar flag (defaults to primary calendar) Read-only operation; never modifies calendar data Output formats include JSON, table, YAML, and CSV for integration flexibility
Research organization and collaboration through Google Workspace integration. Manages research papers, notes, and data across Drive folders, Docs, and Sheets with built-in search and organization commands Logs experiments and findings in shared Sheets, exports data in CSV format for external analysis tools Shares research outputs and announces files to collaborators via Drive and Gmail workflows Requires four utility skills: gws-drive , gws-docs , gws-sheets , and gws-gmail
Unified indexing and search across code repositories, documentation, research papers, datasets, local folders, Slack, and Google Drive. Supports 8+ source types with flexible identifiers (UUID, display name, or URL); index GitHub repos, docs sites, arXiv papers, HuggingFace datasets, local folders, Slack workspaces, and Google Drive with one API Search modes include targeted queries with AI responses, universal hybrid search across all indexed sources, autonomous research (Oracle), and live GitHub code search without indexing Slack integration requires OAuth setup or BYOT; Google Drive supports selective folder/file indexing and continuous sync Built-in dependency analysis, code advisor for best-practice checks, context sharing across agents, and category-based organization for sources Requires NIA_API_KEY environment variable; all operations via shell scripts with environment variable configuration for optional parameters
Web search with LLM-optimized results, relevance scoring, and flexible filtering. Supports four search depth modes (ultra-fast, fast, basic, advanced) with configurable latency and relevance tradeoffs Includes domain filtering, time range constraints, date ranges, country boosting, and raw content extraction Returns results with title, URL, content snippet, and relevance score; optional image results and favicons Automatic OAuth authentication via Tavily MCP server or API key configuration; no manual token management required
gives agents real-time and historical access to front-page headlines across 20 countries for breaking news, current events, and comparative media analysis.
Comprehensive AI-powered research with multi-source synthesis and citations. Produces structured reports grounded in web sources, taking 30-120 seconds depending on model selection (mini for targeted queries, pro for complex comparisons) Supports multiple output formats: markdown reports, JSON with custom schemas, and configurable citation styles (numbered, MLA, APA, Chicago) Includes async workflow for long-running research via --no-wait , status , and poll commands, plus real-time streaming with --stream Best for deep analysis, market reports, literature reviews, and multi-angle comparisons; use tavily-search instead for quick fact-finding
Automated web scraper selecting optimal Actors for 55+ platforms including Instagram, TikTok, YouTube, Facebook, Google Maps, and more. Covers 55+ pre-configured Actors across 8 major platforms with use-case-specific selection guidance (lead generation, influencer discovery, brand monitoring, competitor analysis, trend research) Supports three output formats: quick chat display, CSV export, or JSON export with customizable result limits Includes multi-Actor workflow patterns for complex tasks like lead enrichment, influencer vetting, and competitor deep-dives Dynamically fetches Actor schemas and input parameters via mcpc CLI, then executes runs with automatic error handling and follow-up suggestions
Web search API for LLMs with real-time data access, content extraction, site crawling, and AI-powered research. Five core methods: search() for web results, extract() for URL content, crawl() for site-wide extraction, map() for URL discovery, and research() for end-to-end AI synthesis Supports Python and JavaScript SDKs with async clients for parallel queries and configurable search depth (ultra-fast/fast/basic/advanced) Crawl method accepts semantic instructions to focus extraction on specific content types; Map-then-Extract pattern available for targeted workflows Research method offers three model tiers (mini/pro/auto) with polling-based async execution, streaming support, and structured output schemas Integrates with LangChain, LlamaIndex, CrewAI, Vercel AI SDK, and other frameworks; supports Hybrid RAG patterns and project-level usage tracking
基于 opencli 命令的智能搜索路由器。当用户想要使用 OpenCLI、CLI 或 API 搜索、查询、查找或研究信息时，尤其是涉及指定网站、社交媒体、技术资料、新闻、购物、旅游、求职、金融或中文内容时，务必使用此 skill
Install the CLI. Run your first Skill in 30 seconds. Scale when you're ready.