prompt-hydrator

To convert prompts into execution plans, you need a prompt hydration mechanism that detects task scope, routes actions, and captures deferred work. It transforms terse requests into detailed, multi-step plans for AI agent orchestration by matching intent to predefined workflows.

Task routing in AI agent orchestration is the process of deciding whether to execute a task directly or enqueue it for later. You need it when handling complex, multi-session operations that require triage and sequential task management.

Structuring a multi-step workflow from a single request involves scope detection to identify single-session versus multi-session efforts. The prompt is then decomposed by routing individual tasks, queuing deferred work, and selecting the appropriate workflow from a decision tree.

Yes, prompt hydration requires pre-loaded indexes of skills, workflows, heuristics, and task states. These indexes are necessary to contextualize the user's prompt, detect the scope, and accurately plan the agent's actions.

Yes, you can automate task triage and scope detection by applying prompt hydration to incoming requests. The mechanism identifies multi-session efforts, routes immediate tasks for execution, and queues deferred work for subsequent processing.

The main limitation of prompt hydration for workflow automation is its reliance on pre-loaded indexes of skills and heuristics. Without comprehensive, predefined decision trees and existing task states, the automated task routing and scope detection will lack the necessary context to generate accurate plans.