hackernews-topn-explainer

Analyze Hacker News Top N lists and generate structured Chinese deep-dive documents.

1|Updated Apr 9, 2026

Search Tags:#analysis #chinese #content-generation #structured-output #deep-dive #hackernews #topn

Ready to run

npx skills add https://github.com/tense-i/tensei-skills --skill hackernews-topn-explainer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hackernews-topn-explainer
Source: https://github.com/tense-i/tensei-skills/tree/main/hackernews-topn-explainer
Command: npx skills add https://github.com/tense-i/tensei-skills --skill hackernews-topn-explainer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill converts Hacker News Top N lists into structured Chinese deep-dive documents that explain what posts are about, why they ranked, key discussion points, and actionable follow-ups.

Core Features & Use Cases

Provide a global overview of the top N list and a per-post deep-dive covering content, evidence, and potential impacts.
Explain why each post ranked (signal analysis such as score, timing, topic fit, and community engagement) and summarize representative viewpoints from the discussion.
Generate ready-to-share Chinese analyses suitable for decision-making, research, or training materials.

Quick Start

Input a Hacker News list type and N (e.g., top 20) to generate a structured Chinese deep-dive document for each post.

Frequently Asked Questions about hackernews-topn-explainer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate structured Chinese summaries from Hacker News Top N posts?▼

You can generate structured Chinese summaries by inputting a Hacker News list type and N value, which produces a deep-dive document covering TL;DR, discussion signals, and recommended actions for each post.

What is the best way to analyze Hacker News ranking signals for trending discussions?▼

The best way to analyze Hacker News ranking signals is to evaluate score, timing, topic fit, and community engagement to explain why each post ranked, while summarizing representative viewpoints from the discussion.

Can I extract actionable follow-ups and trend evaluations from Hacker News lists?▼

Yes, you can extract actionable follow-ups and trend evaluations from Hacker News lists by generating a per-post deep-dive that includes content overview, evidence, potential impacts, and recommended actions.

Does this Hacker News analysis approach require real-time API data for structured output?▼

Yes, this Hacker News analysis approach requires real-time data from the Hacker News API to ensure accurate trend summarization, discussion evaluation, and actionable follow-up extraction for the structured output.

What are the limitations of converting Hacker News Top N lists into Chinese deep-dive documents?▼

The primary limitation is the dependency on real-time Hacker News API availability, which restricts analysis to currently trending posts and their active community discussions.