Qingmu Community Listing

The problem

Community profiles often sit in group announcements, social posts, signup forms, and casual introductions. The fields are inconsistent, and the content usually lacks a structured summary that can be cited by AI search. Community Listing helps organize these materials into reviewable Markdown while keeping clear compliance boundaries, such as not collecting phone numbers or private QR codes.

How it works

The skill first identifies the community type, such as alumni groups, chambers of commerce, enterprise communities, or personal interest groups, then collects fields like name, city, activity types, and public contact channels from the matching template. After confirmation, you can choose plain output or GEO-optimized output. The latter favors concrete numbers, keyword-oriented headings, and block-quote summaries, turning vague phrases such as “active” or “large” into more searchable structure without inventing missing data. It then generates {CommunityName}_community_listing.md or {CommunityName}_community_listing_GEO.md and submits it through the IMA upload flow as pending review.

Boundaries

It is suitable for public, compliant community profiles, not for paid intermediation, membership-guarantee promises, or non-compliant transactions. Contact information is limited to official accounts or video channels, and sensitive terms, false claims, or vague details still need further verification. Generated content remains marked as pending review and should not be treated as live.