Kermt Setup
NVIDIA/skills
Bootstrap the KERMT agent environment — verify host docker + nvidia-container-toolkit, build the kermt:latest image from the repo's Dockerfile if it doesn't yet exist, and run a GPU smoke test…
Initialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification.
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install drawthingsai/draw-things-community init-gpu-server --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/init-gpu-server .claude/skills/init-gpu-server && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .claude/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-serverType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install drawthingsai/draw-things-community init-gpu-server --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/init-gpu-server .agents/skills/init-gpu-server && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .agents/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install drawthingsai/draw-things-community init-gpu-server --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/init-gpu-server .cursor/skills/init-gpu-server && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .cursor/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/drawthingsai/draw-things-community.git --path .agents/skills/init-gpu-server--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install drawthingsai/draw-things-community init-gpu-server --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/init-gpu-server .gemini/skills/init-gpu-server && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .gemini/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install drawthingsai/draw-things-community init-gpu-serverInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/init-gpu-server .github/skills/init-gpu-server && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .github/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install drawthingsai/draw-things-community init-gpu-server --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/drawthingsai/draw-things-community.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/init-gpu-server .opencode/skills/init-gpu-server && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "init-gpu-server" agent skill from https://github.com/drawthingsai/draw-things-community/tree/main/.agents/skills/init-gpu-server into .opencode/skills/init-gpu-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "init-gpu-server", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
init-gpu-serverInitialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification.
Init GPU Server is an agent skill from drawthingsai/draw-things-community. Initialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in DevOps & Cloud, covering Containers. It works with CUDA, Docker and NVIDIA AI Platform. The repository describes itself as: The community repository for the Draw Things app. The licence is GPL-3.0.
Read from SKILL.md and the folder at commit 3cac075. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
sshbashapt-getdockerFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use ssh and docker, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Init GPU Server loads about 2.2k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 532 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from drawthingsai/draw-things-community at commit 3cac075, republished under its GPL-3.0 licence (© drawthingsai). 532 words, ~2,203 tokens.
.claude/skills/init-gpu-server/SKILL.md (or your agent's skills folder).Use this workflow when bringing up a new Draw Things GPU server reachable as root@HOST.
Prepare the server for Draw Things GPU workloads:
/root/utils/mnt/models and /mnt/loraModels/mnt/official-modelsRepo source:
Scripts/ServerManagement/GPUScriptImportant files:
update_scripts.sh: uploads files from files_to_copy.txt to /root/utils/init_gpu_server.sh: installs Docker/CUDA/NVIDIA runtime, Python deps, network sysctl, and the Draw Things Docker imageLaunchGPU/remount_disk.sh: historical reference for disk remounting and mergerfs setupverify_gpu_setup.sh: remote verification helperBefore running the init script:
bash -n Scripts/ServerManagement/GPUScript/init_gpu_server.shIf working from an older branch, make sure init_gpu_server.sh has these properties:
export DEBIAN_FRONTEND=noninteractive
apt-get -o DPkg::Lock::Timeout=600 \
-o Dpkg::Options::=--force-confdef \
-o Dpkg::Options::=--force-confold ...CUDA_REPO_ID=$( . /etc/os-release && echo "ubuntu$(echo "$VERSION_ID" | tr -d ".")" )init_server; do not force return 0.ssh -t for automation.read lines tolerate EOF, for example read -p "..." DISK1 || DISK1="".INIT_COMMANDS string.Accept the SSH host key if needed:
ssh -o BatchMode=yes -o ConnectTimeout=10 -o StrictHostKeyChecking=accept-new root@HOST 'echo ok'Upload the GPUScript files:
bash Scripts/ServerManagement/GPUScript/update_scripts.sh root@HOSTExpected remote destination:
/root/utils/Run:
bash Scripts/ServerManagement/GPUScript/init_gpu_server.sh root@HOSTThis should install/configure:
/opt/draw-things-venv with tqdm, schedule, and boto3drawthingsai/draw-things-grpc-server-cli:latestIt is acceptable to skip disk mounting inside this script. Mount disks explicitly after inspecting lsblk.
If apt or dpkg fails on a conffile prompt, such as /etc/cloud/cloud.cfg, repair the remote package state:
ssh root@HOST 'DEBIAN_FRONTEND=noninteractive dpkg --force-confdef --force-confold --configure -a'
ssh root@HOST 'DEBIAN_FRONTEND=noninteractive apt-get -y -f install -o Dpkg::Options::=--force-confdef -o Dpkg::Options::=--force-confold'If a new run hits an apt lock, inspect first:
ssh root@HOST 'pgrep -af apt; pgrep -af dpkg'If an earlier init process is still installing packages, wait. Do not kill package-manager processes unless the user explicitly asks.
Inspect block devices and current mounts before changing disks:
ssh root@HOST 'lsblk -o NAME,SIZE,TYPE,MOUNTPOINTS,FSTYPE,UUID; echo ---; blkid || true; echo ---; df -h'Target shape:
DISK_Ap1 -> /mnt/models
DISK_Bp1 -> /mnt/loraModels
/mnt/models/official-models:/mnt/loraModels/models_extra -> /mnt/official-modelsDo not assume device names. Pick the two 7T data disks from actual lsblk output. On one validated host the mapping was:
/dev/nvme1n1p1 -> /mnt/models
/dev/nvme0n1p1 -> /mnt/loraModelsIf the two 7T disks are raw disks with no partitions and no filesystem, get explicit user approval before partitioning and formatting. This destroys data on those disks.
After approval, replace MODELS_DISK and LORA_DISK with the inspected devices:
ssh root@HOST 'set -euo pipefail
export DEBIAN_FRONTEND=noninteractive
apt-get -o DPkg::Lock::Timeout=600 -o Dpkg::Options::=--force-confdef -o Dpkg::Options::=--force-confold update
apt-get -o DPkg::Lock::Timeout=600 -o Dpkg::Options::=--force-confdef -o Dpkg::Options::=--force-confold install -y parted mergerfs
MODELS_DISK=/dev/nvme1n1
LORA_DISK=/dev/nvme0n1
for disk in "$MODELS_DISK" "$LORA_DISK"; do
test -b "$disk"
if lsblk -nrpo NAME "$disk" | tail -n +2 | grep -q .; then
echo "Refusing to repartition $disk because it already has child block devices" >&2
lsblk "$disk" >&2
exit 1
fi
done
parted -s "$MODELS_DISK" mklabel gpt mkpart primary ext4 0% 100%
parted -s "$LORA_DISK" mklabel gpt mkpart primary ext4 0% 100%
partprobe "$MODELS_DISK" "$LORA_DISK" || true
udevadm settle
mkfs.ext4 -F -L models "${MODELS_DISK}p1"
mkfs.ext4 -F -L loraModels "${LORA_DISK}p1"
'For non-NVMe disks, adjust partition paths accordingly. NVMe partition paths normally use the p1 suffix.
After partitions/filesystems exist, mount them by UUID and persist in /etc/fstab:
ssh root@HOST 'set -euo pipefail
mkdir -p /mnt/models /mnt/loraModels /mnt/official-models
MODEL_PART=/dev/nvme1n1p1
LORA_PART=/dev/nvme0n1p1
MODEL_UUID=$(blkid -s UUID -o value "$MODEL_PART")
LORA_UUID=$(blkid -s UUID -o value "$LORA_PART")
cp /etc/fstab "/etc/fstab.drawthings.$(date +%Y%m%d%H%M%S).bak"
grep -vE "/mnt/models|/mnt/loraModels|/mnt/official-models|/mnt/official_models" /etc/fstab > /etc/fstab.drawthings.new
mv /etc/fstab.drawthings.new /etc/fstab
{
echo "UUID=$MODEL_UUID /mnt/models ext4 defaults,nofail 0 2"
echo "UUID=$LORA_UUID /mnt/loraModels ext4 defaults,nofail 0 2"
echo "/mnt/models/official-models:/mnt/loraModels/models_extra /mnt/official-models fuse.mergerfs allow_other,use_ino,ro,nofail 0 0"
} >> /etc/fstab
if grep -q "^#user_allow_other" /etc/fuse.conf; then
sed -i "s/^#user_allow_other/user_allow_other/" /etc/fuse.conf
elif ! grep -q "^user_allow_other" /etc/fuse.conf; then
echo user_allow_other >> /etc/fuse.conf
fi
mountpoint -q /mnt/official-models && umount /mnt/official-models || true
mountpoint -q /mnt/models || mount /mnt/models
mountpoint -q /mnt/loraModels || mount /mnt/loraModels
mkdir -p /mnt/models/official-models /mnt/loraModels/models_extra /mnt/official-models
mountpoint -q /mnt/official-models || mount /mnt/official-models
lsblk -o NAME,SIZE,TYPE,MOUNTPOINTS,FSTYPE,UUID
df -h | grep -E "Filesystem|/mnt/models|/mnt/loraModels|/mnt/official-models"
'Use /mnt/official-models, not /mnt/official_models, for Draw Things GPU server conventions.
Always verify directly, even if the init script prints success:
ssh root@HOST 'set -e
echo "=== GPUs ==="
nvidia-smi --query-gpu=name,driver_version --format=csv,noheader
echo "=== CUDA ==="
/usr/local/cuda/bin/nvcc --version
echo "=== NVIDIA Container Toolkit ==="
nvidia-ctk --version
echo "=== Docker ==="
docker --version
docker info --format "Runtimes={{json .Runtimes}} Default={{.DefaultRuntime}}"
echo "=== Draw Things image ==="
docker image inspect drawthingsai/draw-things-grpc-server-cli:latest --format "{{.Id}} {{.RepoTags}}"
echo "=== Mounts ==="
lsblk -o NAME,SIZE,TYPE,MOUNTPOINTS,FSTYPE
df -h | grep -E "Filesystem|/mnt/models|/mnt/loraModels|/mnt/official-models"
'Then run an end-to-end Docker GPU test:
ssh root@HOST 'docker run --rm --gpus all nvidia/cuda:12.0.0-base-ubuntu22.04 nvidia-smi'Success means the container sees GPUs through the NVIDIA runtime.
For an 8x RTX 5090 host, a healthy result looked like:
nvidia-smi lists 8 GPUs580.173.02/usr/local/cuda/bin/nvcc --version reports CUDA Toolkit 13.3nvidia-ctk --version reports NVIDIA Container Toolkit 1.19.1nvidia runtimedrawthingsai/draw-things-grpc-server-cli:latest exists locallynvidia-smi successfullylsblk shows both 7T partitions mounted:nvme1n1p1 /mnt/models ext4
nvme0n1p1 /mnt/loraModels ext4df -h shows /mnt/models, /mnt/loraModels, and /mnt/official-modelsIf /var/run/reboot-required exists, tell the user. GPU/Docker may work before reboot, but reboot is the clean final state after kernel, firmware, CUDA, or driver setup:
ssh root@HOST 'test -f /var/run/reboot-required && cat /var/run/reboot-required || echo no'© drawthingsai, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/init-gpu-server of drawthingsai/draw-things-community.
Open the folder on GitHubat commit 3cac075
Init GPU Server next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Init GPU Server this skilldrawthingsai/draw-things-community | 579 | — | ~2.2k | Automated safety check: Pass | GPL-3.0 | |
| Kermt SetupNVIDIA/skills | 3.5k | 1 repos | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Tao Setup Nvidia GPU HostNVIDIA/skills | 3.5k | — | ~3.4k | Automated safety check: Notes | Apache-2.0 | |
| Holoscan Install ContainerNVIDIA/skills | 3.5k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Cuopt InstallNVIDIA/skills | 3.5k | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Tao Run On DockerNVIDIA/skills | 3.5k | — | ~5k | Automated safety check: Warn | Apache-2.0 |
NVIDIA/skills
Bootstrap the KERMT agent environment — verify host docker + nvidia-container-toolkit, build the kermt:latest image from the repo's Dockerfile if it doesn't yet exist, and run a GPU smoke test…
NVIDIA/skills
Host setup for TAO GPU backends. An agent skill from NVIDIA/skills.
NVIDIA/skills
Install Holoscan SDK via the NGC Docker container. An agent skill from NVIDIA/skills.
NVIDIA/skills
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install.
NVIDIA/skills
The Docker execution platform for TAO jobs — a local daemon or a remote GPU box via DOCKERHOST=ssh://user@host.
vllm-project/vllm-skills
Deploy vLLM using Docker (pre-built images or build-from-source) with NVIDIA GPU support and run the OpenAI-compatible server.
drawthingsai/draw-things-community
Generate, benchmark, validate, and troubleshoot LongCat-Video-Avatar 1.5 videos with draw-things-cli.
drawthingsai/draw-things-community
Set up and verify a new Draw Things CPU proxy and Envoy server using the scripts in Scripts/ServerManagement/CPUScript.
drawthingsai/draw-things-community
Use and troubleshoot an already installed Homebrew draw-things-cli for model discovery, authentication, local, cloud, or remote image generation, basic image-to-image and video generation, output…
drawthingsai/draw-things-community
Add a new image or video generative model to the Draw Things app / CLI with a compile-first, end-to-end workflow across SwiftDiffusion, tokenizer plumbing, text encoder, fixed encoder, UNet / DiT…
drawthingsai/draw-things-community
Validate Draw Things LoRA training end to end with draw-things-cli, including tiny-dataset training, loss and scaler checks, checkpoint sanity, and base-versus-LoRA generation comparison.
drawthingsai/draw-things-community
Add or tighten Draw Things LoRA trainer support for generative models available in the Draw Things app / CLI, covering LoRA builders, trainer dispatch, tokenizer and fixed-encoder wiring, checkpoint…
Works with
Categories
Initialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification. Init GPU Server is an agent skill from drawthingsai/draw-things-community. Initialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification.
Init GPU Server fits situations like: tasks that involve Containers.
Run `npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a claude-code`. Or copy the skill folder (.agents/skills/init-gpu-server in drawthingsai/draw-things-community) into .claude/skills/init-gpu-server in your project. Claude Code loads it when a task matches its description.
Run `npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a codex`. Or copy the skill folder (.agents/skills/init-gpu-server in drawthingsai/draw-things-community) into .agents/skills/init-gpu-server in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add drawthingsai/draw-things-community --skill init-gpu-server -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/init-gpu-server, .gemini/skills/init-gpu-server, .github/skills/init-gpu-server and .opencode/skills/init-gpu-server in your project.
Going by SKILL.md and its folder, Init GPU Server needs the command-line tools its instructions call (ssh, bash, apt-get and docker). Our summary lists: Python 3; Docker.
SKILL.md contains no URLs. Its commands use ssh and docker, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Init GPU Server is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Init GPU Server: Kermt Setup (NVIDIA/skills, 3.5k stars), Tao Setup Nvidia GPU Host (NVIDIA/skills, 3.5k stars), Holoscan Install Container (NVIDIA/skills, 3.5k stars) and Cuopt Install (NVIDIA/skills, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
drawthingsai (a GitHub organization) maintains it in drawthingsai/draw-things-community, which has 579 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 6, 2026.
Source: drawthingsai/draw-things-community on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.