Reviewing Grasshopper code with AI
A useful review preserves the input and output contract, explains a proposed change and checks its behavior in Grasshopper.
An AI coding assistant can help organize a Grasshopper review. Begin with the intended operation, expected data structure and a small working example. For a visual definition, describe components and connections; for a script, include the relevant code and inputs.
Ask a bounded question
We would ask where null inputs can occur, which values assume a unit and whether an expensive operation is repeated. Each suggestion is a hypothesis to test in Grasshopper. A text review does not execute the definition or establish that its geometry is correct.
Keep the original and revised outputs together. A cleaner-looking canvas is useful only if the required behavior survives.
Check data grouping as well as geometry
McNeel’s Python guide describes data trees as branches indexed by paths. Converting them to nested lists needs care when path depths differ.
For panels grouped by floor, a filter should preserve the intended floor grouping. Test an empty branch, a missing item and a floor with a different panel count. Compare paths and counts alongside the viewport. Flattening might leave the panels visible while changing a downstream schedule.
Accept one explained change
- State the input and output structure that must remain.
- Ask for one change, its reason and a small verification example.
- Run the same cases before and after, including the awkward input.
- Keep the change only when its behavior can be explained.
This proposed review routine also informs Falcon’s research into definition context and validation. The handover should include a readable definition and an example another designer can run to check that the change preserved the required behavior.