Generate, evaluate, reflect
Astra uses high reasoning to choose nodes, rib connections and rectangular sections within fixed carriage and contact interfaces. CadQuery builds the guide base and two mirrored jaws in an isolated Docker container.
A separate evaluator verifies the exported STEP geometry, checks collisions at nine openings from 20 to 60 mm and tests contact with 20 mm and 60 mm sample gauges. A linear 3D beam-frame solver evaluates pinch, payload, lateral and combined loads.
A review-agent call interprets every measured result and saves the next working policy. After the first two attempts, a generated sizing utility passes independent tests before reuse. Atlas memories and actual tool outputs enter later design prompts. Git versions source and context.
Fixed acceptance checks
Nominal stress ≤ 80 MPa, tip displacement ≤ 0.25 mm, member buckling factor ≥ 2 and running clearance ≥ 0.25 mm. The objective is moving jaw-pair mass; the unchanged guide base is included only in total assembly mass.
Measurement scope
Mass is measured from STEP volume at nominal aluminium density. Structural results use ideal rigid beam joints and fixed carriage roots, with loads applied at the defined tip node. Pad offset couples, fillets, bearings and contact are not modeled. The actuator, friction pads, fatigue, local shear and torsional stresses are outside this study. The drone and mounting adapter are display context; installation and flight loads have not been evaluated.
This sequential study uses the same archive, memory and sandbox services as the full multi-agent workbench. The workbench’s Atlas triggers drive its two-specialist evaluation/reflection queue; this study uses a Python loop. Recorded API usage: $4.39 within a $25 cap.