Results for “sentiment-analysis”

Extract structured review data from Google Maps search results using the BrowserAct API, enabling local business analysis, reputation monitoring, and competitive benchmarking.

Aggregates market-wide sentiment indicators including VIX, Put/Call ratio, Fear & Greed Index, market breadth, and sector rotation to classify the current regime as risk-on, risk-off, or neutral.

research-synthesis

Collects market data from Yahoo Finance and Exa, calculates technical indicators, scans watchlists, and generates market analysis reports to identify trading opportunities.

Analyzes global market conditions across US, European, and Asian indices, forex, commodities, and economic indicators to produce structured market reports with risk sentiment assessment.

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.

Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days).

Analyzes why a piece of content resonates with audiences using five classic communication theories, identifies the emotional core and effective stance, and outputs discussion directions for a chatroom.

Search, analyze, and monitor X/Twitter from the terminal, with support for bookmarks, likes, following, trends, and AI-powered analysis via Grok.

Produces decision-oriented market research, competitive analysis, investor due diligence, and industry intelligence with source attribution.

Conducts thorough landscape research, competitive analysis, best practices evaluation, and evidence-based recommendations. Expert in market research and trend analysis.

Turn accepted search evidence into an intent, competitor, and information-gain brief.

进行市场研究、竞争分析、投资者尽职调查和行业情报，附带来源归属和决策导向的摘要。适用于用户需要市场规模、竞争对手比较、基金研究、技术扫描或为商业决策提供信息的研究时。

Conduct and synthesize customer research into actionable insights from interviews, surveys, reviews, and online communities.

Synthesizes recent conversations about any topic across Reddit, Hacker News, the open web, and optionally X/Twitter into a single briefing with citations, engagement metrics, and cross-platform pattern analysis.

Guides statistical hypothesis testing with assumption checks, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting for research data.

Research companies, industries, or competitor sets using web search and seven analytical lenses to produce structured intelligence for downstream product management tasks.

Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site operators plus recency filters. Produces DISCOURSE.md (a structured brief) and JSON output the writer can consume. Complements blog-researcher (which focuses on authority sources) with a recency-and-engagement lens. Use when user says "blog discourse", "discourse research", "what are people saying about", "research what people are saying", "voice of customer", "social listening", "30-day research", "trend research", "what's the discussion on", "real-time research", "practitioner discourse", "/blog discourse".

Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.

Requires python3, and AISA_API_KEY. Uses the supplied AISA_API_KEY to send requests to https://api.aisa.one. Native-first ClawHub plugin for `trend-forecast`. Ships the packaged AIsa skill with an `openclaw.plugin.json` manifest and a Claude-compatible bundle fallback. 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.