wechat-article-skills
Automates the full WeChat Official Account publishing pipeline—from topic selection through final posting—reducing manual effort and accelerating content vel…
Open-source WeChat Official Account operations assistant: nine skills covering topic selection, drafting, review, formatting, image generation, stickers, and publishing. Works with Claude Code, Cursor, Codex, and 13+ Claw-series agents. Optional .aws config packs exported from aiworkskills.cn set your account voice, formatting themes, and visual styles; without one it uses default styles. Documentation is in Chinese.
- Generate topic ideas from trending keywords, auto-prioritize by engagement potential
- Draft articles from outlines, auto-adjust tone for WeChat audience
- Review and edit copy for consistency against brand guidelines
Automates the full WeChat Official Account publishing pipeline—from topic selection through final posting—reducing manual effort and accelerating content velocity for teams managing Mandarin-language social channels.
Content teams and marketing ops managing WeChat Official Accounts who need to scale publication frequency without proportional headcount increase.
https://github.com/aiworkskills/wechat-article-skills
By aiworkskills
How to Get It
git clone https://github.com/aiworkskills/wechat-article-skills.git # then copy or symlink the nine skills/aws-wechat-article-* directories into ~/.claude/skills/ (or project .claude/skills/)
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
After installing, paste this into Claude:
Help me generate topic ideas from trending keywords, auto-prioritize by engagement potential
Trust Signals Auto-scanned
Community Pulse Growing
Discussed on Reddit
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 54 GitHub stars; contributors unknown; last commit 3d ago; license Apache-2.0.
Things to check
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Evaluation
Scored from trust signals (evidence-eval-v1): 54 GitHub stars; contributors unknown; last commit 3d ago; license Apache-2.0.