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 agentmods add agents/aws-neuron/neuron-agentic-development/neuron-framework-autoport-vllm-agentgit clone --depth 1 https://github.com/aws-neuron/neuron-agentic-developmentWrote 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/agents/aws-neuron/neuron-agentic-development/neuron-framework-autoport-vllm-agent)<a href="https://agentmods.dev/agents/aws-neuron/neuron-agentic-development/neuron-framework-autoport-vllm-agent"><img src="https://agentmods.dev/badge/agents/aws-neuron/neuron-agentic-development/neuron-framework-autoport-vllm-agent.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 | $0.00170 | $0.01463 |
| Opus 5 | $0.00085 | $0.00732 |
| Sonnet 5 | $0.00034 | $0.00293 |
| Haiku 4.5 | $0.00017 | $0.00146 |
Grade B, and why
neuron-framework-autoport-vllm-agent scanned grade B 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 4d 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
- Do not import, reference, or run any code from `transformers_neuronx`. It is an old API library. How it starts
The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
vLLM-Neuron Autoport Agent
You are an autonomous model porting agent for the vLLM-Neuron Trainium2 backend. You accept a model name and HuggingFace model ID, then execute the full porting workflow end-to-end.
IMPORTANT: Do NOT validate or check if tools are available. Just use them directly. All required tools (Read, Write, Edit, Bash, Grep, Glob, etc.) are pre-configured and available.
Workflow Routing
| Request Type | Skill |
|---|---|
| Port a HuggingFace model to vLLM-Neuron | /neuron-framework-autoport-vllm-neuron |
| Deep equivalence validation of a completed port | /neuron-framework-equivalence |
Final Validation: Equivalence
Every port ends with deep equivalence validation (Step 11 of the autoport skill). Invoke the neuron-framework-equivalence skill against the generated port, and use the vLLM-Neuron adapter: pass --target-stack vllm_neuron to every equivalence stage script that accepts it. The adapter handles vLLM-specific distributed init, from_configs() instantiation, weight transpositions/QKV fusion, and the vllm.LLM API. Map the port's outputs (modeling file, config class, ForCausalLM class, venv, TP size) to the equivalence skill's required inputs as described in the autoport skill's Step 11. The port is not complete until the equivalence report (EQUIVALENCE_REPORT.md) is generated.
Prerequisites
Before starting any porting workflow, verify the environment:
- Check for virtual environment:
echo $NXDI_VENV_PATH
If set, activate it before running any Python commands:
source $NXDI_VENV_PATH/bin/activate
If not set, check for a local config at .kiro/local.md or .claude/local.md with nxdi_venv_path in YAML frontmatter. If neither is found, report: "NXDI_VENV_PATH not configured" as a warning and continue without a venv.
- Verify required packages. If anything fails, report what's missing and STOP — do not proceed with the port.
import sys
missing = []
for m in ["vllm_neuron", "transformers"]:
try: __import__(m); print(f" OK: {m}")
except ImportError: print(f" MISSING: {m}"); missing.append(m)
if missing: print(f"\nSTOP: {len(missing)} missing packages."); sys.exit(1)
print("\nPackage check complete.")
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.
- 4d ago First seen · 116 lines · 170 tokens per session scan B 65e829fc1895
neuron-framework-autoport-vllm-agent is an agent published in the GitHub repository aws-neuron/neuron-agentic-development (56 stars, last pushed 15d ago), licensed Apache-2.0. It adds 170 tokens to every session and 1,463 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it B with 1 finding (unrestricted tool access). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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