About this skill

Problem context

When tracking topics across Weibo, Bilibili, Baidu, Zhihu Daily, GitHub, and Hupu, manually switching platforms makes it easy to miss trends and hard to turn scattered hot lists into one comparable view. This is especially noticeable when selecting follow-up topics from Chinese consumer news and technical trends.

How it works

The skill is built for hot-list aggregation:
- Keyword triggers: phrases such as “today's hot topics” or “top 5 Weibo” select different scopes.
- Structured output: --json returns machine-readable fields, making it easier to feed downstream workflows or write into documents.
- LLM summaries: each item can be reduced to a concise 15-character summary that highlights the core message.
- Isolated fallbacks: each source is handled separately, so one failed feed does not block the others, which is useful for first-pass daily briefing material.

Boundaries

It is useful for Chinese trending topics, technical trends, and daily briefing material, but it is not a real-time full-text search tool and does not replace deeper inspection of the original pages. If an API changes, a page requires JS rendering, or a platform is not yet covered, additional parsing logic is needed.

Screenshots

Use Cases

Ops checks Weibo, Bilibili, and Hupu before selecting topics for content briefs.
Analyst pulls unified JSON hot lists across six platforms for daily briefing material.
Tech editor focuses on GitHub trends and creates concise item summaries.
Content team limits output to top five per platform before posting to Feishu.

Best For

Social media ops selecting topics who need quick Weibo, Bilibili, and Hupu hot-list checks.
Daily-brief editors who need multi-platform hot items compressed into outline-ready entries.
Technical analysts tracking GitHub trends who want concise per-item summaries.
Data analysts building monitoring briefs who need a unified JSON structure for filtering or storage.

Related Skills

Customer Insight Analyzer

@user_fc05d2ec/customer-insight-analyzer

Analyzes smart customer-service chat logs with semantic clustering to generate word clouds, Top K frequent questions, and personalized guess-you-ask recommendations.

Data Analysis 2026.08.29 ↓ 363

KeyAPI Reddit Content Analytics

@user_2e47cd26/keyapi-reddit-content-analytics

Maps natural-language Reddit requests to KeyAPI REST workflows, validates endpoint contracts against official docs, and executes search, detail, comment, ranking, and report tasks.

Data Analysis 2026.08.29 ↓ 366

NEP Paper Intelligence Officer

@user_116023ea/nep-watcher

Schedules fetching from NEP and custom academic sites, filters and ranks papers by keywords, generates Chinese summaries, and pushes Feishu cards with local download archiving.

Data Analysis 2026.08.29 ↓ 371

Curve Lab

@user_6bbd6f5f/curve-lab

Browser-based CSV/TXT visualizer with multi-Y-axis curves, smoothing, and PNG/JSON/CSV export.