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This workflow covers bulk context extraction from your entire codebase. Your coding agent reads through your project and curates knowledge in multiple passes, automatically organizing everything into the context tree. For onboarding individual files (1-3 documents), see Onboard Existing Context.

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Prerequisites

  • ByteRover CLI installed
  • Project initialized (run brv to start the REPL and initialize your project)
  • A codebase with existing patterns, conventions, or documentation worth capturing

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Step 1: Curate from Your Codebase

Copy this prompt and paste it into your coding agent’s chat (e.g., Cursor, Claude Code, etc.):
> curate all important context from this codebase using brv curate; focus on:

1. Code Style and Quality
2. Styling and Design
3. Naming Conventions
4. Project Structure and Dependencies

ByteRover should intelligently organize into appropriate domains and topics
Your coding agent will read through your codebase and run brv curate multiple times to capture the knowledge. ByteRover automatically organizes everything into the context tree.

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Step 2: Review Changes

Verify what was added: 
brv status
This shows your context tree changes (added, modified, and deleted files). Your context is already stored locally and ready to query.

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Step 3: Query to Verify

Test that your context is retrievable.
Copy this prompt and paste it into your coding agent’s chat:
> use brv query to retrieve context related to (your intention)
Your coding agent will execute brv query with your query and return the relevant context.
ByteRover will search intelligently, follow relations between topics, and synthesize an answer from your context tree.

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What Happened Behind the Scenes

  1. Autonomous Analysis: ByteRover analyzed your codebase content and detected relevant domains (code_style, testing, structure, api, etc.) using semantic understanding.
  2. Intelligent Organization: Content was organized hierarchically into the context tree at .brv/context-tree/, with appropriate domain and topic structure.
  3. Relation Mapping: ByteRover identified connections between related topics and created explicit @domain/topic relations to build a navigable knowledge graph.
  4. Duplicate Prevention: Before creating new topics, ByteRover searched for existing related knowledge to prevent duplication and update existing topics when appropriate.
  5. Facts Extraction: ByteRover extracted structured facts from your content — categorized as personal, project, preference, convention, team, environment, or other — and stored them in the ## Facts section of each knowledge file. See How Curation Works for details.

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Customizing Your Bootstrap

You can customize how ByteRover processes your codebase: Focus on specific areas: 
> curate context about testing patterns and conventions from this codebase using brv curate
Break into smaller pieces: 
> curate context from this codebase, break it into small focused pieces
Summarize before storing: 
> curate context from this codebase, summarize it before adding
For more customization options, see Curate Context with Intelligence.

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Cloud Sync (Optional)

Push/pull requires a cloud account. See Local vs Cloud for setup.
To share your bootstrapped context with teammates: 
brv push

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Next Steps