
Smart planter unrouted
chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline
P4 results is an open-source printed circuit board by chainstart, from the chainstart/makerai-lab repository on GitHub. It is a 2-layer board with 2 parts on 6 nets.
Its parts include 1 capacitor and 1 IC.
MakerAI is an AI-native hardware runtime and manufacturing platform. The board design path turns reviewed, structured engineering inputs into auditable KiCad schematics and PCBs; it does not treat a rendered image or an autorouter return code as proof that hardware is ready to build.
The sole active EDA implementation is
skills/makerai-board-design. It targets
low-voltage, low-power, low-speed, module-based embedded boards and provides:
The fixed smart-pot MVP and the earlier Hardware-DSL/KiCad script experiment are
archived under legacy/. They are not current design backends.
skills/
makerai-board-design/ Current schematic, PCB, routing, and review skill.
assets/ Schemas, examples, evidence, profiles, and templates.
references/ Engineering policies and workflow documentation.
scripts/ Deterministic generators, checkers, and exporters.
tests/ Fast workflow and policy regression tests.
legacy/
pcb-mvp/ Archived fixed smart-pot manufacturing MVP.
kicad-script-demo/ Archived natural-language/Hardware-DSL EDA prototype.
lab/ Archived tool evaluations and experiment evidence.
reports/ Archived project reports and presentations.
research/ Archived market, module, and ecosystem research.
docs/ White papers, proposals, and design discussions.
reports/ Reports produced by the current skill route.Generated skill environments, downloaded tools, and scratch runs live below the
skill as .venv/, .tools/, and .runs/; they are intentionally ignored by
Git. Reproducible inputs, lock files, source code, and policies are versioned.
The current route keeps concerns separate:
design.json owns components, exact pins, nets, footprints, and constraints.design.evidence.json owns primary-source evidence, assumptions, waivers, and
mandatory human-review boundaries.See the skill instructions, architecture, and professional schematic workflow for the authoritative process.
Bootstrap and verify the isolated EDA environment:
SKILL_DIR="$PWD/skills/makerai-board-design"
"$SKILL_DIR/scripts/bootstrap.sh"
"$SKILL_DIR/scripts/doctor.py" --strict
"$SKILL_DIR/.venv/bin/python" -m pytest -q "$SKILL_DIR/tests"Generate and review the reference ESP32-S3 schematic in a fresh output directory:
SKILL_DIR="$PWD/skills/makerai-board-design"
"$SKILL_DIR/scripts/run_professional_schematic.py" \
"$SKILL_DIR/assets/examples/esp32-s3-sensor-hub.json" \
--profile "$SKILL_DIR/assets/schematic-layouts/esp32-s3-sensor-hub-professional-v1.json" \
--evidence "$SKILL_DIR/assets/examples/esp32-s3-sensor-hub.evidence.json" \
--template-dir "$SKILL_DIR/assets/schematic-templates/blocks" \
--source-catalog "$SKILL_DIR/assets/template-sources.lock.json" \
--output build/esp32-s3-sensor-hub-schematicThe command refuses to overwrite a non-empty output directory. A passing result
is SCHEMATIC_AUTOMATED_REVIEW_PASSED: an engineering-review candidate that
still requires the documented human checks. PCB placement, routing, and release
commands are documented in the skill instructions.
The automated route does not cover mains, high-energy batteries, medical or automotive safety functions, motor power stages, discrete RF, DDR, PCIe, Ethernet PHY layout, isolation barriers, or certification sign-off. Those cases require a qualified engineer and a design-specific review plan.
Never describe an automatically generated design as production-ready. Use these states consistently:
generated: files exist, but required gates have not all passed;review-candidate: automated gates pass and human review remains;release-approved: a named human reviewer completed the release checklist;blocked: at least one required gate failed or the design is outside scope.The archived implementations and their selected outputs remain in
legacy/ so earlier results can be inspected and reproduced.
New features, board families, validation rules, and release decisions must use
the current skill route.
The broader product direction remains documented under docs/, while
historical tool evaluations, reports, and research evidence remain under
legacy/.
The board-design skill source is MIT licensed. Optional upstream tools are kept at process boundaries and retain their own licenses. Review upstream licenses before redistributing tool binaries or copied material.
| Qty | Value | Footprint | References |
|---|---|---|---|
| 1 | 100nF | test:C_0805 | C1 |
| 1 | ACS37010 | test:ACS37010 | IC1 |
2 parts. The full list of its parts is on this page, with links to each part's symbol and footprint where PCBKit's library has them.
From the chainstart/makerai-lab repository on GitHub, at the commit this page was made from: the board is legacy/lab/section6-tool-tests/outputs/PCBSchemaGen-sample-results/p4_results/p4.kicad_pcb. PCBKit opens the board in the browser, with nothing to install.
Its repository states no licence, so its author keeps all rights: ask chainstart before reusing the design.

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

chainstart/makerai-lab
MakerAI hardware-agent research, whitepaper, lab artifacts, and MVP pipeline

hzeller/rpi-rgb-led-matrix
Controlling up to three chains of 64x64, 32x32, 16x32 or similar RGB LED displays using Raspberry Pi GPIO


adamws/kicad-kbplacer
KiCad plugin for automatic keyboard's key placement and routing

Luos-io/luos_engine
Open-source and real-time orchestrator for cyber-physical-systems, to easily design, test and deploy embedded applications and digital twins.

NVNTLabs/switch2-SDEX2M2
Micro SD Express to M.2 NVME Adapter for Nintendo Switch 2

BlueSCSI/BlueSCSI-v2
BlueSCSI v2/Ultra - an open source, open hardware, SCSI emulator using the Pi Pico PR2040 and Pico 2 RP2350

ohmtech-rdi/eurorack-blocks
Software to Hardware Prototyping for Eurorack using C++, Max/Gen~ or Faust
