AI Daily News

Problem

AI news is scattered across papers, product launches, funding, regulation, and open-source repos. Engineers, product managers, investors, and content teams need a consistent way to ask what happened today, yesterday, or on a specific date, and then turn that signal into reusable briefs. This skill addresses that workflow with a unified AI-news dataset and structured follow-up outputs such as tech radar, knowledge-base notes, content materials, product opportunity scans, and investment/strategy briefs.

How It Works

• Default path: For today, latest, or current AI news, use get_latest_news first. It returns the newest available dataset, freshness metadata, local-time display hints, and suggested next steps.
• Date path: For explicit or relative dates such as yesterday or YYYY-MM-DD, use get_news_dataset. The script interprets the date in the user's timezone and resolves it to the canonical dataset date.
• Capability discovery and remote analysis: Use sync_capabilities to discover available platform capabilities, then call advanced analysis with invoke_remote_capability. submit_engagement handles feedback about missing stories, sources, quality issues, or bugs.
• Output modes: The skill can produce Markdown briefings, AI Coding tech radar, knowledge-base capture, content-creation materials, product scans, and strategy summaries. Scheduled jobs can use --automation-safe for structured delivery, while isolated follow-up sessions can use --context-only to load context without rendering the full news view.

Boundaries

It is scoped to AI news and AI industry intelligence, not a general search engine or a full enterprise research system. It targets OpenClaw and Hermes Agent, typically on macOS/Linux with Python 3 available. When timezone differences, freshness gaps, or capability limits exist, rely on display_notice, generated_at_local, and capability status rather than assuming the content is fully current or complete.