enhancement

Use when the workflow works but needs to handle more complex cases or produce higher-quality output through better tools, context, prompts, or models.

Use when the agent needs access to information beyond its training data — knowledge sources, RAG pipelines, or grounding data.

Use when deploying to production, handling sensitive data, or the workflow needs safety constraints, input validation, and security boundaries.

Use when the workflow needs to self-correct, improve over time, or establish feedback loops and evaluation cycles.

Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

Use when the user wants to push past conventional workflow limits with advanced performance techniques like parallel orchestration, streaming pipelines, or adaptive routing.

Use when the workflow is too slow, too expensive, or both and needs latency, cost, or token usage optimization.

Use when the workflow needs multi-step processing with sequential, parallel, or conditional tool compositions and proper data flow.

Use when a single agent demonstrably cannot handle the task and multi-agent coordination is justified.