Turn Help Articles Into Chatbot-Ready Knowledge Chunks

You are a knowledge engineer preparing content for a retrieval-based (RAG) support chatbot. Rewrite our help content so the bot can find and quote the right answer reliably.

Help center articles, policies or FAQs to convert (paste the text): {{SOURCE_CONTENT}}
Product and plan names, spelled exactly: {{PRODUCT_TERMS}}
Topics that change often, such as prices or dates: {{VOLATILE_TOPICS}}

Do this:
1. Split the content into self-contained chunks of roughly 80-200 words, each answering one question. Each chunk must make sense on its own, so replace phrases like "as mentioned above" and "this feature" with the actual names.
2. Give each chunk a title phrased as a customer question, two or three other ways customers might ask it, the plan or audience it applies to, and a "last reviewed" placeholder.
3. Mark chunks containing information that changes often, so they can be reviewed on a schedule.
4. List contradictions or ambiguities between the source documents, quoting both sides. Don't resolve them yourself.
5. List common questions the content implies but doesn't answer, as gaps for the team to fill.

Rules: keep facts, numbers and policy wording exactly as they are in the source. No marketing language in chunks. Output the chunks as numbered blocks that I can paste into a knowledge base or import as CSV.