Claude Swarm — Multi-Agent Orchestration with SDK

What it is

Claude Swarm is a Python-based multi-agent orchestration system built on the Claude Agent SDK. It uses a hierarchical architecture where Claude Opus decomposes complex tasks into subtasks, and Claude Haiku workers execute them in parallel waves. It includes a real-time TUI dashboard for monitoring agent progress and budget control to cap API spending.

Claude Swarm targets developers building AI-powered automation that requires decomposing large problems into parallelizable units of work. Instead of one long-running agent, you get a coordinated team with visibility into cost and progress.

Why it saves time or tokens

A single large-context agent call processes everything sequentially and burns tokens on the full context window. Claude Swarm splits work across smaller, focused agents that each handle a narrow subtask with minimal context. Parallel execution reduces wall-clock time. Budget control prevents runaway costs by capping total spending across all agents.

How to use

1. Install Claude Swarm from the repository
2. Define your task decomposition strategy and worker roles
3. Run the swarm with a task description and budget limit

Example

from claude_swarm import Swarm, Task

swarm = Swarm(
    orchestrator_model='claude-opus-4-20250514',
    worker_model='claude-haiku-3',
    max_budget_usd=5.00,
    max_parallel_workers=4
)

result = swarm.run(
    task='Analyze the top 10 Python web frameworks. '
         'For each, summarize features, performance, '
         'and community size.',
    output_format='markdown_table'
)

print(result.output)
print(f'Total cost: ${result.total_cost:.2f}')

Related on TokRepo

• Multi-agent frameworks — compare multi-agent orchestration tools on TokRepo
• AI tools for agents — autonomous AI agent frameworks

Common pitfalls

• Task decomposition quality depends on the orchestrator model; vague task descriptions produce poor subtask splits
• Parallel workers sharing state requires careful coordination; design subtasks to be independent whenever possible
• Budget limits that are too tight may terminate the swarm before completing all subtasks; estimate costs before setting limits