customaize-agent-create-workflow-command

Multi-step agent workflows can avoid context bloat by isolating detailed instructions in separate task files. Subagents load these file-based prompts on-demand, keeping the orchestrator context lean while executing sequential, parallel, or stateful patterns.

File-based task prompt orchestration is a pattern where detailed subagent instructions are stored in separate files. This isolates context, allowing an orchestrator command to trigger research, design, and coding agents modularly without exceeding token limits.

Yes, agent orchestration supports parallel, sequential, and stateful execution patterns. You can configure multiple subagents to run simultaneously or in ordered steps, with options for specific agent selection and model usage per task.

To create a reusable workflow command, define modular step components that assign tasks to specialized subagents. Store each step's detailed instructions in separate files to enable on-demand loading and reuse across different feature implementation workflows.

Yes, agent orchestration includes options for agent selection and model usage. You can assign specific models to individual subagents within the workflow, ensuring each task step utilizes the appropriate computational resources.

Large workflow commands exceed token limits due to context bloat from embedding detailed instructions directly in the prompt. Isolating these instructions in separate task files for on-demand loading by subagents resolves this limitation.