What problem does it solve?
Manually checking reads, likes, comments, shares, and favorites for published WeChat Official Account articles is repetitive and error-prone. This Skill automates engagement data collection from the WeChat creator center and writes the metrics into a published-content tracking database.
Core Features & Use Cases
- Automated engagement scraping: Uses camoufox-cli with a persistent browser session to open the creator center publish-history page and parse per-article reads, likes, comments, shares, and favorites from page innerText.
- QR-code login management: Self-manages the wx_mp browser session with headless QR-code screenshot login and a stop-and-wait confirmation flow, without exporting cookies or tokens.
- Database integration: Matches scraped articles by title against rows in the published-track pub_wx_mp SQLite table and writes metrics via the update-metrics script, supporting single-article fetch and batch refresh of the latest 20 posts.
- Use Case: Run a daily heartbeat job that calls fetch-all to refresh engagement metrics for all recently published WeChat articles, then use the accumulated data for daily content performance reviews.
Quick Start
Ask the agent to run wx-mp-engagement fetch-all to refresh engagement metrics for all tracked WeChat Official Account articles.