How Agentic Processing Works
When you push your context tree, ByteRover processes it through multi-step reasoning: Domain Detection: Categorizes context into relevant domains (code_style, testing, structure, etc.) using semantic understanding, not keyword matching. Duplicate Prevention: Searches existing knowledge before creating new topics to prevent duplication and suggests updates to related content. Hierarchical Organization: Structures context into domains → topics → subtopics with explicit relations, creating a navigable knowledge graph. Relation Mapping: Identifies and creates explicit links between related topics using@domain/topic notation for intelligent navigation.
Why This Matters
Intelligent, not automatic: Unlike vector similarity systems, ByteRover uses Agentic Search, which understands context semantically and makes reasoned organizational decisions. Hierarchical structure prevents chaos: Knowledge is organized into a clear, browsable hierarchy, not a flat collection of documents. Explicit relations over similarity scores: Relations are intentional and explicit, not based on embedding similarity, making retrieval more reliable. After reviewing locally with/status, push to the remote space:
Managing Context in the Remote Space
The remote space provides tools to:- Review hierarchical structure and relations generated during processing
- Edit topic organization and content to fit your team’s needs
- Refine relations between topics for improved navigation
- Remove or merge duplicate topics
Pull Updates from Remote
Team members sync the organized context tree to their local environment:.brv/context-tree/ directory with the latest organized knowledge.