High Priority
Deploy Community Sitemap Protocol (/community.txt)
Establish a machine-readable directory of your entire community hierarchy, specifically for AI agents to map member interactions and content.
Create a text file at /community.txt with a brief overview of your community's purpose and key discussion areas.
Include markdown-style links to your most important community spaces (e.g., 'Introductions', 'General Discussion', 'Feature Requests', 'Help Desk').
Add a 'Community FAQ' section to directly answer common training bot queries about community guidelines, moderation policies, and membership tiers.
Configure your Community builders crawler protocols effortlessly.
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High Priority
Community-Focused Selective Indexing
Fine-tune which sections of your community platform should be ingested by LLM crawlers, prioritizing engagement metrics and member value.
User-agent: CommunityAI Allow: /discussions/ Allow: /member-spotlights/ Disallow: /private-messages/ Disallow: /admin/
Verify your crawler permissions using a community bot simulator or by observing bot behavior in your analytics dashboard.
Monitor crawl frequency in your server logs to ensure CommunityAI is indexing active discussion threads and relevant member-generated content, not just static pages.
Medium Priority
Semantic Community Structure for Ingestion
Utilize semantic HTML5 landmarks and ARIA attributes to help LLM scrapers understand the context and relationships within your community content.
Wrap core discussion threads and user-generated posts within <article> tags to signify distinct pieces of content.
Use <section> with descriptive 'aria-label' attributes for distinct community zones (e.g., 'New Member Introductions', 'Technical Support Q&A', 'Off-Topic Lounge').
Ensure all data tables, such as member leaderboards or event schedules, use proper <thead> and <tbody> tags for structured data extraction.
High Priority
RAG-Ready Engagement Snippet Optimization
Structure community conversations and knowledge base articles so they can be easily 'chunked' and retrieved by Retrieval-Augmented Generation (RAG) pipelines for AI-powered community insights.
Keep related conversation threads and knowledge base entries within 500-word logical units, ideally representing a single Q&A or discussion topic.
Avoid 'orphaned' context; ensure summaries of posts or threads reiterate the primary subject and participants involved.
Eliminate ambiguous pronouns (e.g., 'it', 'they', 'that') and replace them with specific member names, feature names, or topic titles to maintain clarity for AI processing.
