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Coding agent

The RBS platform includes a built-in AI coding agent — similar to Cursor or Claude Code, but deeply integrated with the build system. It understands your project structure, can build and test targets, modify code, and even spawn teams of specialized AI teammates for complex tasks. The coding agent runs on your branch server and is accessible from your code editor or the integrated terminal.

Quick start

What makes it different

Build system aware

Natively understands your BUILD.rbs files, targets, dependencies, and toolchains.

Multi-agent teams

Spawn teams of specialized AI teammates (frontend, backend, tester, etc.) for large tasks.

Deep code tools

Read, write, search, and precisely edit files. Run terminal commands. Build and test targets.

Fully extensible

Define custom tools, prompts, teammate roles, and skills using the RBS DSL.

Features

Code understanding and editing

The agent can read, search, and precisely edit your source files:
The agent will:
  1. Scan your project structure and understand the build graph.
  2. Read the relevant source files.
  3. Make targeted edits using precise string replacement (not full file rewrites).
  4. Run tests to verify the changes.

Build system integration

Unlike standalone coding assistants, the RBS agent has native build tools:
The agent can:
  • Build targets: rbs_build — compile and package code.
  • Run tests: rbs_test — execute test targets and report results.
  • Run applications: rbs_run — start and interact with running targets.
  • Scan the project: rbs_scan — discover all packages, targets, and dependencies.
  • Query the build graph: rbs_query — analyze dependency relationships.
  • Manage processes: rbs_start / rbs_stop — run servers in the background.

Interactive commands

Extended thinking

For complex reasoning tasks, the agent supports extended thinking:
When enabled, you’ll see the agent’s reasoning process:

Multi-agent teams

For large, multi-faceted tasks, the agent can spawn teams of specialized AI teammates that work in parallel.

How teams work

Each teammate:
  • Has its own runtime with full access to all tools.
  • Receives a role-specific system prompt.
  • Communicates via a shared message bus.
  • Reports progress and results back to the orchestrator.

Coordination models

  • Hierarchical (default): You direct all teammates. Best for structured tasks.
  • Collaborative: Teammates coordinate with each other. Best for exploratory tasks.

Built-in roles

You can also define custom teammate roles using the Agent SDK.

DAG workflows

For multi-step tasks with dependencies, the agent can define and execute DAG workflows where each step is a subagent:
Each node runs as an independent subagent, receives context from upstream nodes, and passes results downstream.

Rules enforcement

The agent automatically loads project rules and coding standards from your repository: Rules are injected into the agent’s system prompt and periodically re-reminded during long sessions.

Example .agent-rules/coding-standards.md

Session persistence

All agent sessions are automatically saved on the branch server:
You can resume past sessions and review what the agent did:

Server API

The coding agent is accessible via REST and WebSocket APIs, enabling integration with any editor or tool:

REST endpoints

WebSocket streaming

Responses stream in real-time over WebSocket, including:
  • Text deltas (agent’s response).
  • Tool call events (what the agent is doing).
  • Thinking events (extended reasoning).
  • Team events (teammate progress).

CLI flags

Examples

Basic usage

Code changes

Build and test

Team-based tasks

Next steps

Agent SDK

Define custom tools, prompts, teammate roles, and skills.

Agent Builder SDK

Build your own agents for voice, chat, automation, and IoT.