Retrieve wiki vault pages via progressive loading and wikilink traversal for cross-domain queries.
npx skills add https://github.com/ShaheerKhawaja/ProductionOS --skill wiki-rag
Please help me install this Agent Skill. Skill: wiki-rag Source: https://github.com/ShaheerKhawaja/ProductionOS/tree/main/skills/wiki-rag Command: npx skills add https://github.com/ShaheerKhawaja/ProductionOS --skill wiki-rag
Progressive retrieval-augmented context from the SecondBrain wiki vault, enabling cross-project understanding across domains with structured drill-down and graph traversal.
Start the wiki-rag skill to load contextual pages from the SecondBrain vault for a cross-domain query.
High-intent search queries and answers about installing and using this skill.
Graph RAG improves wiki context retrieval by traversing wikilinks to surface related nodes and their summaries, enabling cross-project understanding across multiple domains. This graph-based loading method provides structured drill-down for complex research and planning tasks.
Progressive loading in local RAG manages wiki context by sequentially querying a hot cache, then the index, domain pages, and individual pages. This tiered context retrieval ensures responsive performance when fetching information from a wiki vault.
Yes, you can use wiki rag to answer questions touching multiple knowledge domains. It retrieves relevant context from a SecondBrain wiki vault to support cross-project reasoning, fetching linked pages and summaries to build comprehensive contextual understanding.
To retrieve context from a wiki vault using wikilink traversal, start the wiki-rag skill with a cross-domain query. It performs graph-based context loading by following wikilinks between pages to surface related nodes and their summaries for research.
You should use graph-based context loading instead of standard vector embeddings when answering cross-project questions or building context for planning tasks. Graph RAG traverses wikilinks to surface related nodes, providing structured drill-down across multiple domains.
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