Daily Newspaper is a skill published by agensi that instructs an AI agent to act as a digital newsroom. Given a prompt, the agent fetches real-time news, verifies timestamps, scores stories by importance, deduplicates across sections, and rewrites content in a neutral inverted-pyramid journalistic style. The output is a single, self-contained HTML file with no external dependencies — multi-column layout, serif typography, and print-aware CSS pagination included.
Coverage spans world, national, and local news, and the skill accepts configuration for specific cities, states, and topic areas such as finance, technology, or sports. Front-page story selection and section layout are handled automatically according to the importance scoring logic built into the skill’s editorial framework.
The skill is designed to address common failure modes when asking a general-purpose AI to summarize news: hallucinated stories, stale data, inconsistent formatting, and lack of source prioritization. By embedding a structured editorial process, it constrains the agent to prioritize reputable sources and primary reporting while rejecting fabricated content.
The resulting HTML file is suitable for display on tablets or for physical printing. No external stylesheets, fonts, or scripts are fetched at read time. This skill has no registered package identifier or repository URL in the current facts, so installation details depend on the host agent platform.