PCBBench library
PCB design guides
Practical ways to check AI-generated circuits, native design files and manufacturing outputs. Each guide explains the evidence to collect, common failure modes and where automated checks stop.
Evaluation
- How to evaluate an AI PCB design toolA practical evaluation protocol for AI PCB tools: native files, electrical checks, routing, cost and reproducibility.
- How to measure the cost of AI PCB designMeasure AI PCB design cost using all attempts, tool expenses, human corrections and successful completion.
- Reproducible benchmarks for AI hardware designDesign a reproducible hardware benchmark with versioned inputs, pinned tools, independent graders and auditable attempts.
- Data contamination in AI PCB benchmarksReduce benchmark leakage with held-out designs, task families, provenance and controlled public examples.
- Pass rate, pass@k and reliability in PCB benchmarksUnderstand first-attempt success, repeated-attempt success and reliability without confusing their denominators.
Schematics
- How to test AI schematic generationTest an AI-generated schematic for electrical intent, real components, valid connectivity and reproducible verification.
- KiCad ERC checklist for AI-generated schematicsReview electrical-rule results without hiding connection mistakes, changing severity settings or overlooking wrong component values.
- Netlist equivalence for AI schematic validationValidate pin-level circuit intent while allowing equivalent drawing layouts and legitimate alternative implementations.
Layout
- How to evaluate AI PCB placement and routingAssess AI PCB layouts with connectivity gates, fixed manufacturing rules and electrical placement constraints.
- How to build a fair PCB autorouter benchmarkCompare PCB autorouters with fixed inputs, completion checks, DRC gates and explicit routing-quality metrics.
- KiCad DRC checklist before PCB fabricationA practical DRC review covering rule profiles, zone refill, unconnected items, exclusions and schematic parity.
Simulation
Libraries
- How to validate an AI-generated PCB footprintCheck an AI footprint against the exact package drawing, pad numbering, assembly process and mechanical envelope.
- From datasheet to KiCad symbol: validation checklistValidate generated KiCad symbols using exact pin tables, electrical types, package variants and footprint mapping.
Components
Manufacturing
Review
- PCB design review checklist for AI outputsReview AI-designed PCBs across requirements, exact parts, connectivity, layout, manufacturing and evidence.
- How to validate PCB engineering change ordersValidate AI-assisted PCB edits with a defined change contract, connectivity diffs and regression checks.
- Reviewing AI-generated PCB power suppliesCheck power-tree requirements, device conditions, component identity and layout assumptions in generated circuits.
- USB-C PCB design review checklistReview USB-C connector identity, power roles, interfaces and mechanical details in AI-generated PCB designs.
- How to review an AI-generated ESP32 PCBReview exact ESP32 variant, power, boot, programming, radio and footprint assumptions in a generated design.
- How to review an AI-generated STM32 PCBReview exact STM32 part and package, power domains, clocking, boot behavior and debug access.
Bring-up
Looking for evaluation details? Read the benchmark methodology or explore the task suites.