Refine a plan#
Prerequisites: an initialized dashboard and a completed planning stage. Outcome: change the intended part of a task, then review all affected outputs.
Choose the right stage#
Change you want |
Send feedback to |
Downstream work |
|---|---|---|
Reorder or add a subtask |
Task Decomposer |
Recipes, parameters, and vision are updated |
Change controllers or their priority |
Skill Generator |
Parameters and vision are updated |
Change a distance, angle, force, or timing value |
Parameter Setter |
Updated parameters continue to vision |
Correct a point on the displayed captured image |
Vision Module |
Annotations are refined; regenerate the script |
Refinement updates the selected stage and its downstream outputs.
Request a change#
Wait until the workspace is idle.
Describe the desired change in natural language.
Optionally include a subtask, parameter, or exact value if you have one in mind.
Submit to that stage’s feedback control.
Review the updated stage and every affected downstream stage.
Generate a new script only when grounding is current.
Feedback can express a high-level intent without naming a controller or giving an exact value. For example:
Can you lift the cube a bit higher?
If you want a specific adjustment, you can also write:
In subtask 3, increase the lift offset by 0.04 m. Keep the grasp timing and the approach subtask unchanged.
Both forms are supported. Subtask numbers and numeric values are optional; the agents interpret the request using the current plan and conversation context. Review the updated plan to check that the resulting adjustment matches your intent.
When a refinement fails#
Read the error, inspect the current stage output, and resolve any reported configuration or response-format issues before retrying. If an otherwise valid update does not match your intent, give further feedback.
A complete parameter response uses a JSON object containing skills.
The application validates that field and checks the parameterized plan before
accepting it.
Verify: the requested change appears in the current output, downstream grounding has completed successfully, and a newly generated script reflects it. See model troubleshooting.