「social」の検索結果

HARD BLOCK — never use for prediction-market/Polymarket UpDown queries; route to okx-dapp-discovery when a named DApp (Polymarket/Aave/Hyperliquid/PancakeSwap/Morpho) appears with a timeframe, or 涨跌/updown for BTC/ETH/SOL/XRP/BNB/DOGE/HYPE. Otherwise, read-only on-chain DEX data, 6 groups: TOKEN (search, hot/热门, liquidity, holders/whale, risk metadata, cluster/持仓集中度, trade history, top traders); MARKET (price/价格, K线/OHLC, index price, wallet PnL/胜率, trade history); SIGNAL (smart money/KOL/whale tracking, buy signals/信号, leaderboard/牛人榜); SOCIAL (news/新闻, sentiment/情绪, token vibe/热度, KOL leaderboard); TRENCHES (pump.fun/meme launches/新盘/扫链, dev reputation, bundle/sniper detection/捆绑狙击者, co-investor — read-only; buy/snipe → okx-dapp-discovery); WS (onchainos ws CLI, or custom WebSocket script/脚本). Also owns Market API payment/x402, quota/额度, and MARKET_API_*_OVER_QUOTA/confirming:true for all 6 groups.

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Transform CHANGELOG entries into social content (LinkedIn, Twitter/X, Newsletter, Slack) in FR + EN. Use after releases or weekly to generate ready-to-post content from guide updates.

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Scrapes posts from any public Facebook Page or personal Profile timeline, returning structured data including post text, author info with profile picture, engagement metrics (likes/comments/shares), full reaction breakdown (Like/Love/Wow/Haha/Sad/Angry/Care as both array and flat counts), hashtags and external links, media assets with full thumbnail URLs and dimensions, page ad library status, and collaborators. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count comment count share count from Facebook, Facebook post bulk export, Facebook social media analytics, get profile picture, get page ad library status, fetch Facebook collaborators. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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Scrapes tweets from X (Twitter) by search query, user handle, or direct URL — returns full tweet data including text, author info, engagement metrics, media, and hashtags. Use when user mentions X, Twitter, tweet scraping, scrape tweets, get tweets, fetch tweets, twitter data, x.com data, tweet collector, tweet search, twitter search, social media scraping, twitter handle scraping, scrape user tweets, from:username, twitter keyword search, hashtag search, twitter timeline, twitter list scraping, collect twitter posts, export tweets, tweet analysis, twitter monitoring, search twitter, get twitter data, twitter api alternative, tweet dump.

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Scrapes posts from any public Facebook Page timeline, returning structured data including post text, author info, engagement metrics (likes/comments/shares), reaction breakdowns (like/love/haha/wow/sad/angry/care), hashtags and external links, and media type. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count/comment count/share count from Facebook, Facebook post bulk export, Facebook social media analytics. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.

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This skill helps users extract structured data from Reddit posts and comments via BrowserAct API. Agent should proactively apply this skill when users express needs like analyzing competitor mentions on Reddit, tracking brand sentiment in Reddit comments, extracting Reddit discussions for market research, finding popular Reddit posts by keywords, monitoring community feedback on specific topics, gathering user reviews from Reddit threads, searching for Reddit posts within a specific date range, sorting Reddit discussions by relevance or hotness, compiling nested Reddit comments for deep analysis, building a structured dataset of Reddit conversations, discovering trending topics in specific subreddits, or monitoring social media activity for specific brands on Reddit.

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This skill helps users extract GitHub repository project details and contributor contact information using keywords, stars, and update dates. Agent should proactively apply this skill when users express needs like search for GitHub projects by keywords, find top open-source contributors in specific domains, extract developer contacts from GitHub repositories, discover trending repositories with high stars, gather contributor profiles and social links for tech recruiting, retrieve GitHub project descriptions and metrics, build developer communities by finding active contributors, search for repositories updated recently, collect personal website and Twitter links of developers, generate targeted leads for developer tools, or track active open-source contributors for collaboration.

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用于搜索英文社交平台，包括 Reddit 帖子、Twitter/X 推文和 YouTube 视频。

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用于搜索中文社交平台。脚本入口覆盖 B站视频、知乎问答和抖音视频；小红书、微博当前没有脚本入口，只能通过 browser-use / 公开网页兜底。

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搜索社区、社媒、新闻热点、百科趋势、开发者生态和技术讨论时使用。

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Access 2,000+ AI models and API tools through one MCP interface for inference, media generation, search, scraping, embeddings, social data, and structured retrieval. Use sandbase_discover before building custom integrations or declaring external data inaccessible; prefer an existing dedicated tool or API key when the user already has one.

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Hunt account takeover taxonomy — 9 distinct paths to ATO, plus chains. Paths: (1) password reset flaws (host-header injection redirects token, predictable/numeric token, Referer leak, no-expiry/reuse), (2) email change without re-auth, (3) OAuth account-link CSRF, (4) MFA bypass (per hunt-mfa-bypass), (5) session fixation, (6) JWT manipulation (forge token to another identity; crypto details → hunt-jwt-crypto), (7) password change without step-up (chain with login timing/length oracle), (8) social-recovery / security-question brute-force, (9) SSO subdomain takeover at OAuth redirect_uri. Chains: cookie theft + password oracle + no step-up = persistent ATO; lax redirect_uri = auth-code theft; dangling-CNAME takeover at redirect_uri = ATO. Validate: demonstrate real takeover of test account B from attacker A's session; OOB/Collaborator confirm blind token-leak steps. Use when hunting ATO chains, testing password reset / email change / MFA / OAuth / session / JWT, or chaining primitives toward Critical.

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Hunting skill for csrf vulnerabilities. Built from 15 public bug bounty reports including modern variants — SameSite=Lax sibling-subdomain bypass (Argo CD CVE-2024-22424), GraphQL mutations-via-GET (GitLab $3,370), framework-wide CSRF middleware disabled (Stripe Dashboard $5,000), path-traversal CSRF-token bypass (GitHub Enterprise CVE-2022-23732 $10k), Origin-omission bypass (TikTok $2,500), OAuth-state null-byte (Streamlabs), WebSocket CSRF / CSWSH (Coda), default-SameSite email-change → ATO (YoYo Games $400), social-account-link CSRF (HackerOne), JSON-CSRF via text/plain on email-change (TikTok $500). Use when hunting modern CSRF — heavy emphasis on chain-to-ATO patterns.

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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.

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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

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Agent D4 - Measurement Instrument Developer - Scale construction and psychometric validation. Covers item development, validity evidence, and reliability testing for social science research.

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Writes expert academic paper summaries for social science research, particularly political science and applied statistics. Use when asked to summarize, review, or create a reading summary of an academic paper, PDF, or research article. Accepts a file (PDF or text format) or a directory of papers. Produces a structured markdown summary — approximately 400–600 words — covering primary contributions, major questions and answers with point estimates, methods and data, and limitations and robustness. Includes BibTeX citation retrieved from Google Scholar and keyword metadata.

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Review research code for reproducibility and quality, extract the paper's main empirical claims, compare paper to code, and write a constructive markdown report. Designed for social science / economics projects with LaTeX papers and Stata, R, or Python code.

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Interactive setup wizard that configures a new project for the social-science-research plugin. Asks the user questions about their field, institution, journals, datasets, key researchers, and R color palette, then writes the answers into references/domain-profile.md and CLAUDE.md. Make sure to use this skill first whenever a user is starting fresh or wants to configure the plugin. Triggers include: "set up my project", "configure the plugin", "run setup", "initialize this project", "I just installed the plugin", "set my field", "set my institution", "configure my domain profile", or any request to personalize the plugin for a specific research context.

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This skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.

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This skill should be used when the user asks to "search for academic papers", "find working papers on SSRN", "look up a DOI", "download paper PDF", "check open access availability", "search NBER papers", "find arXiv preprints", or "search CrossRef". Provides unified search, metadata retrieval, and PDF download across arXiv, NBER, SSRN, CrossRef, OpenAlex, Unpaywall, and Semantic Scholar. Covers economics, finance, social science, CS/AI, and all academic disciplines.

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This skill covers Bayesian estimation and inference in quantitative social science. Use when the user is specifying priors, running MCMC, diagnosing chain convergence, or reporting posterior summaries — including hierarchical models, Bayesian structural models, and small-sample settings where priors regularize. Triggers on "Bayesian estimation", "Bayesian inference", "MCMC", "Markov chain Monte Carlo", "Stan", "PyMC", "NumPyro", "prior", "posterior", "credible interval", "Bayesian structural", "Bayesian BLP", "Bayesian DSGE", "hierarchical model", "random effects Bayesian", "posterior predictive check", "Bayes factor", "prior predictive check", "NUTS", "HMC", "Hamiltonian Monte Carlo", "R-hat", "rhat", "effective sample size", "ESS", "Bayesian calibration", "posterior distribution", "prior elicitation", "weakly informative prior", "brms", "rstanarm", "cmdstanpy", "pymc", "arviz".

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Cost-benefit analysis. Produces economic NPV and financial NPV side by side, with BCR, optimism bias (with mitigation), Marginal Excess Tax Burden, real-terms rebasing, WELLBY / QALY / VPF wellbeing valuation, sensitivity, switching values, EANC for unequal-life options, validation gate, and a one-line headline verdict (socially worthwhile vs financially self-sustaining). Backed by the greenbook R package (HM Treasury Green Book primitives) when available, with graceful fallback. Supports HMT Green Book, EU Better Regulation, World Bank, ADB, and Victorian HVHR. Reads a longlist markdown file directly via --from.

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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.

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