Track and synthesize current AI hotspots into a bilingual HTML daily report. Use when the user says "AI热点", asks for AI日报/AI日报 HTML/AI hot topics, or wants the best recent AI products, papers, viewpoints, and cognition-shifting items from AI/news aggregators.
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Use this skill to produce a high-signal AI daily report, not a raw hot-list dump.
When the user says AI热点, treat it as:
Find new AI-related products, papers, viewpoints, and cognition-shifting materials from the tracked sources. Pick the best 10. If an item is longer than 1000 Chinese characters or roughly 700 English words, summarize it in <=100 Chinese characters plus the link. Return a detailed bilingual AI daily report in HTML page format.Default delivery: do not paste the full HTML source into chat. Save a polished HTML report under .local/ai-hotspots/reports/ai-daily-YYYY-MM-DD.html, then respond with a compact Markdown digest and a file link. Paste raw HTML only if the user explicitly asks for source code.
If the user asks to schedule it every morning, create an automation only after the wake-up time is clear.
Read references/source-list.md for the default source set and source roles.
Use the listed aggregators as discovery surfaces. For factual or technical claims, follow primary sources before ranking when possible:
Do not treat social posts or aggregator summaries as final truth.
Pick exactly 10 items unless the user asks for another count. Prefer:
Rank for the user's current priorities:
Demote items that are only funding/news hype, duplicate commentary, thin product marketing, or unverifiable rumor.
Create a complete HTML page. Keep it readable as a standalone browser page, not as a code snippet in chat.
Required sections:
AI Daily / AI 日报 - YYYY-MM-DD;Visual requirements:
Use concise Chinese first, English second. Do not pad bilingual text if English adds no value; translate the core judgment, not every word mechanically.
If the report includes materials that deserve later reading, also add them to .local/LEARNING_MATERIAL_CANDIDATES.md using the existing S/A/B/Unread convention from the research material workflow.
If access fails, mark the source or item as unread. Never pretend a source was read.
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