Results for “soc”

Monitors websites, RSS feeds, and e-commerce pages for content changes and price drops, with social listening and custom scraping for competitive intelligence and market research.

Cross-platform 30-day social research on a topic — Reddit, X/Twitter, Hacker News, Polymarket, open web. Clusters mentions by narrative, ranks by velocity, and surfaces the contrarian thread with traction.

Extracts business contact details from Google Maps search results and place detail pages, then visits each business website to collect emails, phone numbers, and social media profiles.

Access 83 unified crypto data endpoints covering CEX/DEX markets, on-chain SQL across 80+ blockchain tables, wallet labels, prediction markets, social intelligence, news, and DeFi metrics via a local HTTP API with per-call billing.

Diagnoses social threats and rewards across five domains to improve organizational, team, and product experiences.

Researches a leader's organizational affiliations and fetches logos, producing a JSON record for logo strips and social-proof sections.

Monitors trending topics across 35+ platforms, aggregates trends, analyzes sentiment, and provides real-time notifications via MCP tools.

Analyze political, economic, social, technological, environmental, and legal forces to identify external opportunities and threats for strategic planning.

Extract full article contents from WeChat using the BrowserAct API, with keyword search and date filtering.

Personal investigator / people lookup skill. Deep background research on any person using public records, court documents, property records, social media, corporate filings, and web OSINT. Use when asked to look up, investigate, research, or find information about a person — including court records, traffic infractions, property ownership, career history, social media profiles, corporate affiliations, family connections, and contact details. Also use for "find everything about [person]", "background check", "dig up info on", "what can you find on", or any people-search request.

Extract a TikTok user's profile info and paginated video list with full metadata by navigating to their profile page.

Extracts structured article details and full content from Zhihu search results via the BrowserAct API, with keyword and date filtering.

Queries CDC open data and WHO Global Health Observatory indicators for public health intelligence, covering disease surveillance, vaccinations, and mortality.

Research any topic across Reddit, X, and the web from the last 30 days, then synthesize findings into actionable insights and copy-paste-ready prompts.

Extract paginated TikTok video search results for a given keyword, including author details, engagement stats, music info, and video metadata.

Simulates a complete international journal peer review process with 5 dynamically configured reviewers, producing structured editorial decisions and revision roadmaps.

Diverga Dashboard - Live configuration status and feature overview. 24 specialized agents across 9 categories for social science research. VS methodology prevents mode collapse. Human checkpoints enforce human-in-the-loop decisions. Triggers: /diverga, diverga dashboard, diverga status

Extracts structured data from Reddit posts and comments via the BrowserAct API for competitor analysis, brand sentiment tracking, and market research.

Map user Jobs-to-Be-Done with functional, emotional, and social dimensions plus outcome expectations to reframe product decisions around user motivations.

Coordinates a 13-agent team for rigorous academic research on any topic, supporting eight modes from quick briefs to systematic reviews with meta-analysis.

Collects every tweet in an X (Twitter) conversation thread given a conversation id, returning normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and reply mapping.

Correlate findings across OSINT sources—username enumeration, email lookups, social media profiles, domain records, breach databases, and dark-web mentions—into unified intelligence profiles with confidence scoring and link analysis.

Research the last 30 days across Reddit, X, YouTube, TikTok, Instagram, Hacker News, Polymarket, GitHub, and grounded web search. Returns a ranked, clustered brief with citations. Use when the task needs recent social evidence, competitor comparisons, launch reactions, trend scans, or person/company profiles.

Coleta a linguagem literal do público em avaliações, fóruns, redes sociais, tickets de suporte e transcrições de vendas para gerar um banco de frases verbatim que orienta a escrita de copy.

Multi-signal trend forecasting for autonomous agents. Combines prediction market odds, Twitter/X social sentiment, news velocity, and stock market data into a unified trend analysis with confidence scoring. Powered by AIsa — one API key, five data streams. Use when: the user needs X/Twitter research, monitoring, posting, or engagement workflows.

Searches and reads X (Twitter): profiles, timelines, mentions, followers, tweet search, trends, lists, communities, and Spaces. Publishes posts, likes/unlikes tweets, and follows/unfollows users after the user completes OAuth in the browser. Use when the user asks for Twitter/X research, social listening, posting, or account interactions without sharing account passwords.

Analyzes competitor products by synthesizing data from pricing pages, app store reviews, job postings, SEO signals, and social media into structured competitive intelligence. Produces feature comparison matrices, SWOT analyses, positioning maps, UX audits, pricing breakdowns, action plans, and presentations.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

Generate academic research proposals for PhD applications. Use when user asks to "write a research proposal", "create PhD proposal", "generate research plan", "撰写研究计划", "写博士申请", "doctoral proposal", or mentions specific research topics for PhD application. Supports STEM, humanities, and social sciences with field-specific adaptations. Follows Nature Reviews-style academic writing conventions. Supports both English and Chinese output based on user preference.