agent-coordination

Coordinate multiple agents by selecting a parallel execution pattern, assigning distinct agent roles (code-reviewer, test-runner, etc.), defining quality gates between phases, and managing explicit context handoffs. This pattern executes independent tasks concurrently across Python, JavaScript, Java, Go, Rust, and C# ecosystems to produce validated software changes.

Agent coordination supports five patterns: parallel execution for independent tasks, sequential dependency chains for ordered phases, swarm-style multi-perspective analysis, hybrid multi-phase workflows combining patterns, and iterative refinement loops. Each pattern requires clearly defined agent roles and phase-based quality gates.

Yes, agent coordination works across Python, JavaScript, Java, Go, Rust, and C# ecosystems. Multi-language compatibility enables orchestrating agents that handle code review, testing, and validation across heterogeneous development environments with unified quality gates.

Quality gates are validation checkpoints inserted between workflow phases that ensure artifact readiness before advancing to the next stage. They validate outputs from one agent's work before passing context to dependent agents, preventing invalid intermediate results from cascading.

Sequential coordination chains agents in dependent order, where each phase completes before the next begins. Swarm coordination runs multiple agents in parallel on the same problem from different perspectives, synthesizing results to improve analysis quality and coverage.

Yes, agent coordination requires clearly defined agent roles—such as code-reviewer, test-runner, or analyzer—assigned before workflow execution. Each agent's responsibility must be explicit so context handoffs between phases produce validated, artifact-ready changes.