What is vllm-ascend-serving?

A service manager for running one vLLM Ascend online inference service on a prepared remote container. vLLM Ascend is software for serving language models through a network-accessible service on Ascend hardware.

Use it to launch, check, restart, or stop a single-node vLLM Ascend service, including when another workflow needs to start one.

It provides a defined way to start, restart, inspect, and stop the model service without manually managing remote commands.

How maoxx241/vllm-ascend-workspace configures Claude Code and Codex

Reuse

Borrowing it

Nothing to install: this file belongs to maoxx241/vllm-ascend-workspace. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/maoxx241/vllm-ascend-workspace/main/.agents/skills/vllm-ascend-serving/SKILL.md

Clone the repo

git clone --depth 1 https://github.com/maoxx241/vllm-ascend-workspace

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving/github.svg)](https://agentmods.dev/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving)

Your own site

<a href="https://agentmods.dev/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving"><img src="https://agentmods.dev/badge/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving"><img src="https://agentmods.dev/badge/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-serving.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 3,410 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 44
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

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	$0.00084	$0.03410
Opus 5	$0.00042	$0.01705
Sonnet 5	$0.00017	$0.00682
Haiku 4.5	$0.00008	$0.00341

Measured 7d ago against content hash 35f44f42ce52, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

vllm-ascend-serving 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 7d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/_common.py, scripts/serve_probe_npus.py, scripts/serve_start.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.agents/skills/vllm-ascend-serving/SKILL.md · 260 lines

How it starts

The opening of the file, as written. The whole thing — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.

vLLM Ascend Serving

Manage the lifecycle of a single-node colocated vllm-ascend online service on an isolated VAWS session container.

The optional prepared-runtime MCP has a separate binding/execution lifecycle. Its bindings are not legacy session records and must not be fed to serve_start.py --session-id. In that mode use the coordinator's request/preflight/activate/heartbeat/release sequence and existing remote-dev job tools, with pinned source, declared service ports and a new service process. The legacy wrappers here are not yet transparent adapters for pool bindings. Do not allocate a second local NPU lease for the pool run.

Remote substrate rule: use .remote-dev remote tools for ad hoc remote read/edit/bash/search/patch work around a service. Use this skill for the domain service lifecycle contract and keep its scripts as the compatibility backend for managed VAWS sessions.

This skill takes structured parameters, handles all SSH escaping and remote execution internally, and returns machine-readable JSON. The agent never needs to construct raw shell commands for service management.

Use this skill when

the user asks to start / launch / pull up a vllm-ascend service in a managed session
the user asks to restart or relaunch a service (possibly with changed flags or env)
the user asks to check if a running service is alive / ready
the user asks to stop a running service
another skill needs to start a service (e.g. ascend-memory-profiling)

Do not use this skill when

the task is adding, verifying, repairing, or removing a machine (use machine-management)
the task is syncing code to the remote container (use remote-code-parity)
the task is running benchmarks (a separate skill's responsibility)
the task is offline inference
no session exists yet for the target (use session-management first)

Critical rules

Serving is session-only. serve_start.py, serve_status.py, and serve_stop.py take an optional --session-id <id> / --session-file <path>. When both are omitted, the session is auto-resolved by walking up from the current working directory to the nearest .vaws-local/current-session.json worktree binding — running from inside a session worktree needs zero target arguments. If no binding is found, the command fails fast with instructions to pass --session-id or create a session with session-management's session_create.py.
start automatically runs remote-code-parity before launching. If parity fails, start is blocked.
status and stop do not require parity.
Each session reads and writes only .vaws-local/sessions/<id>/serving.json and never stops another session's service.
start / stop operations for the same session are serialized with a serving lock; different sessions remain independent.
Once a remote PID is launched, serve_start.py writes serving.json with status=starting before health probing so serve_stop.py can clean up even if readiness later fails.
Service ports are always allocated and released through the session lease mechanism — there is no ad-hoc free-port scanning.
Managed serving and relaunch require a nonempty live NPU lease matching the session snapshot before touching an existing service. Free cards are never selected as a fallback for an empty lease, and a stale session.json is not trusted after its live lease was released.
All remote execution goes through the scripts — never construct raw SSH commands for serving.
Keep local runtime state under .vaws-local/sessions/<id>/.
Progress on stderr as __VAWS_SERVING_PROGRESS__=<json>, final result on stdout as JSON.
With a unified workspace alias, new runtime directories use .vaws-runtime/serving/<alias>/<timestamp>/ and the service receives VAWS_AGENT_ID, VAWS_AGENT_ALIAS, and VAWS_PROJECT_ALIAS. Without an alias, preserve the legacy layout.

Read the full file on GitHub · 260 lines

Files

What ships with it

10 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.

Changes

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.

7d ago Changed · +56 lines 35f44f42ce52
11d ago First seen · 204 lines · 84 tokens per session scan A 0c61fd42b72e

Subscribe to this mod's changes

vllm-ascend-serving is a skill published in the GitHub repository maoxx241/vllm-ascend-workspace (36 stars, last pushed 6d ago), licensed MIT. It adds 84 tokens to every session and 3,410 once invoked, about $0.0004 per session on Opus 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.

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