parallel-agents

You orchestrate multiple AI agents for complex code analysis by using parallel and sequential execution with context passing. This allows specialized agents to handle distinct domains like security, performance, and code quality simultaneously.

Multi-agent orchestration coordinates specialized AI agents to execute complex software engineering tasks. It breaks down large problems into manageable subtasks, allowing diverse domain experts to collaborate and synthesize comprehensive findings.

Yes, you can use native Claude Code agent invocation alongside built-in agents like Explore and Plan for sequential feature implementation. Context passing between agents ensures that downstream tasks build directly upon upstream findings.

Perform a comprehensive security audit by assigning one agent to review vulnerabilities and another to assess performance. You can then synthesize their parallel findings into a single report, or have a test-engineer agent generate component tests based on the audit results.

Yes, multi-agent orchestration supports parallel execution for large codebase reviews. You can deploy multiple agents to analyze different perspectives concurrently, significantly streamlining comprehensive analysis that a single agent cannot achieve alone.

A single agent lacks the diverse domain expertise required for complex code reviews, limiting analysis depth. Multi-agent orchestration overcomes this by distributing tasks across specialized agents for security, backend, and frontend perspectives.