爆款文章分析

Overview

Use this skill to fetch hot WeChat Official Account article data by sector and generate a daily analysis report. It is for sector-level or keyword-level analysis, not exact historical scraping for one specific account.

The bundled script queries the hot-article data source, merges keywords by sector, deduplicates articles, ranks them, and writes:

• data.json: raw structured data
• report.html: a minimal visual analysis report with KPI cards, bar charts, ranked article cards, writing style analysis, hot reasons, and writing references

Do not default to Markdown reports. The primary user-facing artifact is report.html.

Quick Start

Run with the default sectors:

python3 ~/.codex/skills/baokuan-article-analysis/scripts/daily_sector_trends.py \
  --output-dir ./output/baokuan-article-analysis

Run custom sectors:

python3 ~/.codex/skills/baokuan-article-analysis/scripts/daily_sector_trends.py \
  --sector 'AI Agent=AI Agent,智能体,Agent框架' \
  --sector 'Skill=skill,Skills,AI Skill' \
  --sector 'Claude Code=Claude Code,Codex,AI编程' \
  --output-dir ./output/baokuan-article-analysis

Run with a JSON config:

python3 ~/.codex/skills/baokuan-article-analysis/scripts/daily_sector_trends.py \
  --sector-config ~/.codex/skills/baokuan-article-analysis/references/default-sectors.json \
  --days 7 \
  --output-dir ./output/baokuan-article-analysis

Workflow

1. Identify sectors and keywords from the user request.
2. If the user only gives broad sectors, use or adapt references/default-sectors.json.
3. Run scripts/daily_sector_trends.py.
4. Open the generated report.html.
5. Summarize for the user:
   • highest-reading and highest-sharing articles
   • writing style patterns
   • hot article reasons
   • title and topic formulas
   • practical writing references
6. Return the HTML file path as the main artifact.

Script Options