
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
Sensor node autorouted is an open-source printed circuit board by chainstart, from the chainstart/makerai-lab repository on GitHub. It is a 2-layer board of 60 × 38 mm with 22 parts on 9 nets, routed with 91 tracks and 5 vias.
Its parts include 3 ICs, 1 capacitor, 1 resistor, 1 diode and 1 connector. It belongs with the home automation and IoT and sensors and measurement boards of this library.
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 |
|---|---|---|---|
| 8 | TestPoint | TestPoint_Pad_D1.0mm | TP1, TP2, TP3, TP4, TP5, TP6, TP7, TP8 |
| 4 | M3 | MountingHole_3.2mm_M3 | H1, H2, H3, H4 |
| 3 | Fiducial | Fiducial_1mm_Mask2mm | FID1, FID2, FID3 |
| 1 | 10uF | C_0805_2012Metric | C1 |
| 1 | 330R | R_0805_2012Metric | R1 |
| 1 | 3V3_REG | SOT-223-3_TabPin2 | U3 |
| 1 | I2C_SENSOR | SOIC-8_3.9x4.9mm_P1.27mm | U2 |
| 1 | LED | LED_0805_2012Metric | D1 |
| 1 | MCU_TQFP32 | TQFP-32_7x7mm_P0.8mm | U1 |
| 1 | POWER_UART | PinHeader_1x04_P2.54mm_Vertical | J1 |
It measures 60 × 38 mm and has 2 copper layers, 1.6 mm thick.
22 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/kicad-script-demo/runs/full-eda-smoke/sensor_node_autorouted.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

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