byterover

Store and recall project knowledge in local Markdown context trees.

Updated Mar 27, 2026
One-click install
npx skills add https://github.com/jangtrinh/EaseUI-Agent --skill byterover-jangtrinh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: byterover
Source: https://github.com/jangtrinh/EaseUI-Agent/tree/main/.claude/skills/byterover
Command: npx skills add https://github.com/jangtrinh/EaseUI-Agent --skill byterover-jangtrinh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a local, persistent memory management system for AI agents, enabling recall of patterns, decisions, and architectural rules using a lightweight brv knowledge base.

Core Features & Use Cases

  • Local knowledge storage: Keeps project context in .brv/context-tree/ as Markdown files for easy review and sharing.
  • Query & curate workflows: Use brv query to retrieve relevant context and brv curate to save new memories or decisions.
  • Offline-first operation: No authentication required for local use; cloud sync is optional for backups.

Quick Start

Use the brv query tool to recall relevant patterns and then run brv curate to save new memories from this session.

Frequently Asked Questions about byterover

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I store and recall project context for AI agents across sessions?

You can store and recall project context for AI agents by using a local knowledge base. This system organizes patterns, decisions, and architectural rules in a local `.brv/context-tree/` directory as Markdown files for easy review across sessions.

How does local memory management for AI agents work without authentication?

Local memory management for AI agents works offline-first without authentication by storing project context locally in `.brv/context-tree/`. You can optionally enable cloud sync for backups, but local operation requires no authentication.

What is the best way to curate and query architectural decisions for AI knowledge management?

The best way to curate and query architectural decisions is using the `brv query` and `brv curate` workflows. `brv query` retrieves relevant context, while `brv curate` saves new memories or decisions from your current session.

Can I review and share the knowledge base used by my AI agent locally?

Yes, you can review and share the knowledge base used by your AI agent. The system keeps project context in `.brv/context-tree/` as Markdown files, which are stored locally for easy review and sharing.

How to persist architectural rules and project patterns for AI agents between different projects?

To persist architectural rules and project patterns for AI agents between projects, use a lightweight knowledge base. It organizes these decisions locally in `.brv/context-tree/`, providing persistent recall across different projects and sessions.