Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add dominodatalab/domino-claude-plugin/plugin install domino-claude-pluginWrote 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/dominodatalab/domino-claude-plugin/environments)<a href="https://agentmods.dev/skills/dominodatalab/domino-claude-plugin/environments"><img src="https://agentmods.dev/badge/skills/dominodatalab/domino-claude-plugin/environments/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/dominodatalab/domino-claude-plugin/environments"><img src="https://agentmods.dev/badge/skills/dominodatalab/domino-claude-plugin/environments.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 | $0.00061 | $0.01668 |
| Opus 5 | $0.00030 | $0.00834 |
| Sonnet 5 | $0.00012 | $0.00334 |
| Haiku 4.5 | $0.00006 | $0.00167 |
Grade D, and why
domino-environments scanned grade D with 2 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 10d 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.
# Run as root if needed Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
&& rm -rf /var/lib/apt/lists/* How it starts
The opening of the file, as written. The whole thing — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domino Compute Environments Skill
Description
This skill helps users create, customize, and manage Domino Compute Environments - Docker-based containers that define the tools, packages, and configurations for workspaces, jobs, and other executions.
Activation
Activate this skill when users want to:
- Create or customize a compute environment
- Install packages or dependencies
- Configure Dockerfile instructions
- Understand environment best practices
- Troubleshoot environment build issues
What is a Compute Environment?
A Domino Compute Environment is a Docker container image that contains:
- Operating system and base tools
- Programming languages (Python, R)
- IDEs (Jupyter, VS Code, RStudio)
- Libraries and packages
- Custom configurations
Domino Standard Environments (DSEs)
Domino provides pre-built environments with common tools:
| Environment | Includes |
|---|---|
| Domino Standard Environment | Python 3.9, R 4.1, Jupyter, VS Code |
| Domino Spark Environment | Spark 3.x, PySpark |
| Domino Ray Environment | Ray for distributed computing |
| Domino GPU Environment | CUDA, cuDNN, GPU libraries |
Creating a Custom Environment
Via Domino UI
- Go to Environments in Domino
- Click Create Environment
- Configure:
- Name: Descriptive name
- Base Image: Start from DSE or custom image
- Dockerfile Instructions: Add customizations
- Click Build
Dockerfile Instructions
Add instructions to customize the environment. Do NOT include FROM statement.
# Install system packages
RUN apt-get update && apt-get install -y \
libpq-dev \
graphviz \
&& rm -rf /var/lib/apt/lists/*
# Install Python packages
RUN pip install --no-cache-dir \
pandas==2.0.0 \
scikit-learn==1.3.0 \
tensorflow==2.13.0
# Install R packages
RUN R -e "install.packages(c('tidyverse', 'caret'), repos='https://cloud.r-project.org')"
# Set environment variables
ENV MODEL_PATH=/mnt/artifacts/model.pkl
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.
- 10d ago First seen · 271 lines · 61 tokens per session scan D bad478c820d9
domino-environments is a skill published in the GitHub repository dominodatalab/domino-claude-plugin (6 stars, last pushed 2mo ago), licensed MIT. It adds 61 tokens to every session and 1,668 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it D with 2 findings (asks for root, recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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