> For the complete documentation index, see [llms.txt](https://docs.uptiq.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.uptiq.ai/agent-builder/build/execution-plan-checklist.md). # Execution Plan/Checklist A checklist is a reusable execution plan automatically generated and refined by the agent over time based on successful runtime plans. It represents a structured sequence of skill executions the agent can reuse when handling similar requests in the future. Instead of planning every request from scratch, the agent can recognize familiar patterns and follow an existing checklist to execute the workflow more consistently and efficiently. If no suitable checklist exists for an incoming request, the planner dynamically creates a new execution plan at runtime. Checklists also power the **Plan** tab on the Builder Canvas. When no checklist exists for the agent, the Plan tab displays **Plan is not available**. *** ## Manage Agent → Checklists Access this section from: **Manage Agent → Checklists** The page displays all execution checklists currently available to the agent. *** ## The Checklists Table The right panel contains a table with the following columns: | Column | Description | | --------------- | ----------------------------------------------------------- | | **Name** | The checklist name | | **When to use** | The type of requests or situations the checklist applies to | | **Steps** | Number of execution steps in the workflow | | **Actions** | Available management actions for the checklist | Each row represents one reusable execution workflow available to the agent. ## How Checklists Are Created Checklists are derived from the agent’s runtime planning behavior. As the planner executes tasks successfully, recurring execution patterns can be converted into reusable checklists. This allows the agent to standardize workflows that are repeatedly used and improve execution consistency over time. Rather than manually rebuilding the same workflow repeatedly, the agent can reuse a known execution structure for similar requests. *** ## How Checklists Relate to the Rest of the Agent ### Builder Canvas → Plan Tab The **Plan** tab visualizes the checklist flow associated with the agent. When one or more checklists exist, the tab displays the execution sequence and step structure. Without any checklists, the Plan tab remains empty. *** ### Skills & Capabilities Each checklist step executes a skill attached to the agent. A checklist can only invoke skills that are currently available within the agent’s configured capabilities. *** ### Triggers Triggers determine **when the agent starts running**. Checklists determine **how the agent executes once it starts**. These systems operate independently: * A trigger can invoke the agent without matching a checklist * A checklist can execute regardless of how the agent was triggered *** ## When Checklists Become Useful Checklists are most valuable when: * Similar requests are received repeatedly * The workflow requires multiple skills executed in a specific order * Runtime planning results have become inconsistent * Execution paths need to be easier to review, explain, or audit * Predictable execution is more important than planner flexibility *** ## When Dynamic Planning Is Better Dynamic planning remains useful when: * Incoming requests are highly varied * The agent is still early in adoption and usage patterns are unknown * Workflows frequently change * A request type is too infrequent to justify a reusable execution plan *** ## Why This Matters Checklists help balance flexibility with execution consistency. The runtime planner is capable of dynamically generating workflows for almost any request, but dynamic plans may vary between runs depending on context and reasoning decisions. For recurring workflows where the ideal execution path is already known, reusable checklists provide: * More predictable execution * Faster runtime planning * Better operational consistency * Easier debugging and auditing * Clearer visibility into how the agent handles common requests Most agents initially operate well without checklists. Over time, as repeated execution patterns emerge, reusable plans become valuable for stabilizing and scaling agent behavior. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. 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