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 security-scangit 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/security-scan)<a href="https://agentmods.dev/skills/seeed-projects/seeed-jetson-developtool/security-scan"><img src="https://agentmods.dev/badge/skills/seeed-projects/seeed-jetson-developtool/security-scan.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.01472 |
| Opus 5 | $0.00020 | $0.00736 |
| Sonnet 5 | $0.00008 | $0.00294 |
| Haiku 4.5 | $0.00004 | $0.00147 |
Grade A, and why
security-scan scanned grade A with 1 finding 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 3d 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 rootlowPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt-get update Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security X-ray Scan Knife Detection
Execution model
Run one phase at a time. After each phase, verify the expected result before continuing.
- If a phase succeeds → print
[OK]and move to the next phase. - If a phase fails → print
[STOP], consult the failure decision tree, and ask the user before retrying.
Phase 1 — Verify prerequisites
Hardware required:
- 1-2x Raspberry Pi 4B
- reComputer J1010 (or J1020, J2011, J2012, AGX Xavier)
- HDMI display, mouse, keyboard
- All devices on the same network
# On Raspberry Pi: check Python version (need 3.9.2)
python3 --version
# On reComputer: check JetPack
cat /etc/nv_tegra_release
Expected: Python 3.9.2 on RPi; JetPack 4.6.1 on reComputer.
Phase 2 — Set up Raspberry Pi environment
# Update system
sudo apt-get update
sudo apt-get upgrade
# Install dependencies
sudo apt-get install python3-pip libjpeg-dev libopenblas-dev libopenmpi-dev libomp-dev
# Install setuptools and Cython
sudo -H pip3 install setuptools==58.3.0
sudo -H pip3 install Cython
# Install gdown for Google Drive downloads
sudo -H pip3 install gdown
# Install PyTorch 1.11.0 (Buster OS, aarch64)
gdown https://drive.google.com/uc?id=1gAxP9q94pMeHQ1XOvLHqjEcmgyxjlY_R
sudo -H pip3 install torch-1.11.0a0+gitbc2c6ed-cp39-cp39-linux_aarch64.whl
rm torch-1.11.0a0+gitbc2c6ed-cp39-cp39-linux_aarch64.whl
Verify PyTorch:
import torch as tr
print(tr.__version__)
Install remaining dependencies:
# Tritonclient
pip3 install tritonclient[all]
# TorchVision 0.12.0
gdown https://drive.google.com/uc?id=1oDsJEHoVNEXe53S9f1zEzx9UZCFWbExh
sudo -H pip3 install torchvision-0.12.0a0+9b5a3fe-cp39-cp39-linux_aarch64.whl
rm torchvision-0.12.0a0+9b5a3fe-cp39-cp39-linux_aarch64.whl
# OpenCV
pip3 install opencv-python
Expected: All packages install without errors.
Phase 3 — Set up reComputer J1010 (Triton Server)
Ensure JetPack 4.6.1 is installed on the reComputer.
# Create model repository and download ONNX model
mkdir -p ~/server/docs/examples/model_repository/opi/1
# Download model.onnx from: https://drive.google.com/file/d/1RcHK_gthCXHsJLeDOUQ6c3r0RlAUgRfV/view
# Place model.onnx into ~/server/docs/examples/model_repository/opi/1/
# (Optional) Clone general Triton server examples
git clone https://github.com/triton-inference-server/server
cd ~/server/docs/examples
sh fetch_models.sh
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.
- 3d ago First seen · 155 lines · 40 tokens per session scan A 05a2227fa661
security-scan is a skill published in the GitHub repository Seeed-Projects/Seeed-Jetson-DevelopTool (54 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 1,472 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
agent-platform-rag-engine-management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google…
agent-platform-model-registry
Agent Platform Model Registry Management. Use when you need to upload, list, describe, update, or delete machine learning models (and their versions) in the Agent Platform Model Registry. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform models.
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
google-cloud-solution-agentic-analytics-spark-knowledge-catalog
Discovers requirements and generates guidance to design and deploy a governed, secure agentic-analytics solution for data that's distributed across Google Cloud, other cloud providers, or on-premises. Data that's outside Google Cloud (such as data from Databricks, Snowflake, Salesforce, SAP, or Oracle systems) is…
training-check
Interactively monitor training metrics from the current Codex session, periodically checking WandB or fallback logs for NaN, divergence, plateaus, and broken runs.
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.