eugr/spark-vllm-docker is a Docker setup for running vLLM, an inference server for serving AI models, on DGX Spark computers. It supports single machines and multi-node clusters for model inference, with startup scripts and configuration for distributed hardware. The catalogue instruction provides an operational runbook for preparing hosts and running repository recipes.
Borrowing it
Nothing to install: this file belongs to eugr/spark-vllm-docker. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/eugr/spark-vllm-docker/main/AGENTS.mdgit clone --depth 1 https://github.com/eugr/spark-vllm-dockerWrote 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/instructions/eugr/spark-vllm-docker/agents-md)<a href="https://agentmods.dev/instructions/eugr/spark-vllm-docker/agents-md"><img src="https://agentmods.dev/badge/instructions/eugr/spark-vllm-docker/agents-md/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/instructions/eugr/spark-vllm-docker/agents-md"><img src="https://agentmods.dev/badge/instructions/eugr/spark-vllm-docker/agents-md.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 | $0.00346 | $0.00346 |
| Opus 5.5 | $0.00138 | $0.00138 |
| Sonnet 5.5 | $0.00069 | $0.00069 |
| Haiku 4.5 | $0.00035 | $0.00035 |
Grade A, and why
spark-vllm-docker AGENTS.md scanned grade A with 0 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 2mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Agent Instructions
These instructions apply to the entire repository.
Repository
This project provides Bash and Python orchestration for running vLLM on one or
more NVIDIA DGX Spark systems. Work from the repository root and read README.md
for the public project overview.
Choose One Guide
- Use or operate the repository: For host preparation, recipe selection,
cluster discovery, image or model setup, recipe launches, and live-server
verification, follow
docs/AGENT_RUNBOOK.md. - Develop the repository: For inspection, fixes, features, reviews, tests,
or changes to scripts, recipes, mods, Dockerfiles, and documentation, follow
docs/AGENT_DEVELOPMENT.md. - Both: Follow the development guide first. Use the operational runbook afterward only when the user also requested a real build, download, or launch.
Read only the guide relevant to the task unless the work crosses that boundary.
A recipe --dry-run used to validate generated commands is development. A
non-dry recipe run, --setup, discovery, image preparation, model download, or
container launch is operation.
Common Boundaries
- Inspect before changing repository, host, container, or cluster state.
- Preserve unrelated user changes and existing local configuration or artifacts.
- Do not expose credentials or
.envcontents in chat, logs, diffs, or commands. - Operational tasks do not authorize source changes. Development tasks do not authorize real deployments. Perform both only when the user requests both.
- Do not prune, overwrite, stop, remove, or force-refresh existing resources unless the requested task requires it.
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.
- 2mo ago First seen · 36 lines · 346 tokens per session scan A 3722699d489b
spark-vllm-docker AGENTS.md is an instructions file published in the GitHub repository eugr/spark-vllm-docker (2,472 stars, last pushed yesterday), licensed MIT. It adds 346 tokens to every session, about $0.0014 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
spark-vllm-docker AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| spark-vllm-docker AGENTS.mdeugr/spark-vllm-docker | Instructions file | 2.5k | yesterday | MIT | A | 346 | Codex, OpenCode |
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| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |