analyze-trends-historical

News trend analysis compares current article mentions against stored historical data to identify emerging themes and declining subjects. This Skill calculates topic velocity and trajectory, generating narrative summaries of the overall trend landscape for weekly stakeholder reports.

Trend velocity analysis quantifies how quickly topics are rising or falling in popularity by comparing current entity extraction data against historical baselines. It pinpoints new subjects gaining traction and old ones fading away, providing measurable trajectory analysis for processed articles.

A Memory MCP server is required for historical data retrieval and entity extraction from processed articles. The Skill depends on this memory storage to compare current mentions against past data, calculate trend velocity, and generate narrative summaries of emerging and declining topics.

Generate weekly reports by processing current articles and comparing them against historical data stored in memory. The Skill identifies the most significant shifts in coverage, highlights key emerging technologies, and pinpoints topics becoming less relevant using velocity and trajectory analysis.

Topic modeling and news analysis require access to a Memory MCP server for historical data retrieval. Without this dependency, the Skill cannot compare current article mentions against past data to calculate trend velocity or identify emerging and declining subjects.

Historical data comparison provides the baseline needed to measure trend velocity and identify trajectory shifts in news coverage. By comparing current mentions against stored historical entity data, the Skill determines which emerging topics are gaining traction and which declining subjects are fading.