AI Workbench for Designers: How Designers Should Work With AI
Explains why AI tools for designers should behave as durable workbenches, not just chatbots, image generators, or automatic drafting plugins.
sketchup-agent-harness
9 public items tagged sketchup-agent-harness.
Bridge Trace: Why Execution Should Be Planned Before Calling SketchUp
Explains why SketchUp execution should be planned as a bridge trace before calling the Ruby bridge, so agent actions remain inspectable and repairable.
Why design_model.json Has to Come Before the SketchUp Scene
Explains why the SketchUp scene is an execution view while the structured design model is better for agent reasoning, validation, repair, and replay.
How to Verify an Agent Harness
Explains why an agent harness needs headless smoke, live bridge checks, release smoke, and installed package verification.
From MCP Server to SketchUp Ruby Bridge
Explains how the MCP server, execution trace, JSON-RPC, Ruby bridge, and feedback loop turn natural language into executable operations.
Making Imports Repairable: From Source Evidence to Working Truth
Explains why plan import should preserve source evidence and generate repairable working truth instead of promising perfect recognition.
Runtime Skill Boundaries in an Agent Harness
Explains the product boundary between product runtime skills, project dynamic skills, and maintainer development skills.
Semantic Component Registry for Agent Placement
Explains why a SketchUp agent needs a semantic component registry that exposes placement intent, constraints, and reuse rules instead of only searching 3D model assets.
Why the Agent CLI Is Only the Entry Point
Explains why Codex and Claude are entry points while the durable SAH core is the MCP server, project workspace, bridge trace, and SketchUp bridge.