Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Seeed-Projects/Seeed-Jetson-DevelopTool --skill deploy-deepseek-mlcgit clone --depth 1 https://github.com/Seeed-Projects/Seeed-Jetson-DevelopToolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-deepseek-mlc)<a href="https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-deepseek-mlc"><img src="https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/deploy-deepseek-mlc/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/deploy-deepseek-mlc"><img src="https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/deploy-deepseek-mlc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00055 | $0.01346 |
| Opus 5.5 | $0.00022 | $0.00538 |
| Sonnet 5.5 | $0.00011 | $0.00269 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade D, and why
deploy-deepseek-mlc scanned grade D with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt update Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
sudo apt install -y nvidia-container curl curl https://get.docker.com | sh Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
# JetPack 6.x — also install curl, then Docker How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploy DeepSeek on Jetson with MLC
Execution model
Run one phase at a time. After each phase:
- Relay all command output to the user.
- If output contains
[STOP]→ stop immediately, consult the failure decision tree below. - If output ends with
[OK]→ tell the user "Phase N complete" and proceed to the next phase.
Prerequisites
| Requirement | Minimum |
|---|---|
| Hardware | reComputer J4012 (Jetson Orin NX 16GB) or equivalent |
| RAM | >8 GB (16 GB recommended for DeepSeek-R1 7B+) |
| JetPack | 5.1.1+ (JetPack 6.x preferred) |
| Storage | SSD strongly recommended — model weights are large |
| Internet | Required for Docker pull and model download |
Phase 1 — Preflight
Verify JetPack version, available RAM, and disk space before touching Docker.
cat /etc/nv_tegra_release
free -h
df -h /
df -h /ssd 2>/dev/null || true
Expected: L4T R35.x (JP5) or R36.x (JP6), ≥8 GB RAM free, ≥50 GB disk available. [OK] when all three pass. [STOP] if RAM or disk is insufficient.
Phase 2 — Install Docker + nvidia-container
sudo apt update
# JetPack 5.x
sudo apt install -y nvidia-container
# JetPack 6.x — also install curl, then Docker
sudo apt install -y nvidia-container curl
curl https://get.docker.com | sh
sudo systemctl --now enable docker
# Add current user to docker group
sudo usermod -aG docker $USER
newgrp docker
Verify:
docker --version
docker run --rm --runtime nvidia --gpus all ubuntu:22.04 nvidia-smi
Expected: nvidia-smi output shows the Jetson GPU. [OK] when GPU is visible inside the container.
Move Docker storage to SSD (strongly recommended)
Edit /etc/docker/daemon.json:
{
"data-root": "/ssd/docker",
"runtimes": {
"nvidia": {
"path": "nvidia-container-runtime",
"runtimeArgs": []
}
}
}
sudo systemctl restart docker
docker info | grep "Docker Root Dir"
[OK] when Docker Root Dir points to your SSD path.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 170 lines · 55 tokens per session scan D 159619b1d50e
deploy-deepseek-mlc is a skill published in the GitHub repository Seeed-Projects/Seeed-Jetson-DevelopTool (56 stars, last pushed yesterday), licensed MIT. It adds 55 tokens to every session and 1,346 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it D with 3 findings (asks for root, downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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