wiki-write-articles

Automated wiki article writing uses a two-agent research and writer workflow to gather evidence from indexed corpus data and produce polished, citation-backed content. It selects topics using entity inventories and SEO data to generate publish-ready articles.

A two-agent research and writer workflow generates citations by having a research agent gather evidence from indexed corpus data, while a writer agent produces content with inline citations anchored to source chunks and cross-linkable entity references.

Yes, generating wiki articles with this workflow requires an available search index and topic inventory. It leverages QMD, Qdrant, and SEO data to select relevant topics and gather citations from the indexed corpus.

Yes, you can use Claude Code sessions to research and write wiki articles automatically. The workflow requires separate Claude Code sessions for the research agent and the writer agent, plus environment variables for any backend services.

The best way to select wiki topics using entity inventories and SEO data is through an automated workflow that surfaces relevant topics and evidence from Qdrant and QMD indexed corpus data before drafting the article.

Limitations of automated wiki article generation include the strict requirement for a pre-existing search index, topic inventory, and configured environment variables for backend services, meaning it cannot generate content from unindexed or unstructured data sources.