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.
curl -O https://raw.githubusercontent.com/maoxx241/vllm-ascend-workspace/main/.agents/skills/vllm-ascend-pd-serving/SKILL.mdgit clone --depth 1 https://github.com/maoxx241/vllm-ascend-workspaceWrote 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/maoxx241/vllm-ascend-workspace/vllm-ascend-pd-serving)<a href="https://agentmods.dev/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-pd-serving"><img src="https://agentmods.dev/badge/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-pd-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.
<a href="https://agentmods.dev/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-pd-serving"><img src="https://agentmods.dev/badge/skills/maoxx241/vllm-ascend-workspace/vllm-ascend-pd-serving.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.00639 |
| Opus 5 | $0.00049 | $0.00319 |
| Sonnet 5 | $0.00020 | $0.00128 |
| Haiku 4.5 | $0.00010 | $0.00064 |
Grade A, and why
vllm-ascend-pd-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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
vLLM Ascend PD Serving
Operate one prefill/decode deployment across an existing Session Group whose members have distinct session IDs. Reuse single-node Serving for each vLLM process; this Skill owns only cross-service role configuration, ordering, proxy health, rollback, and end-to-end smoke.
Preconditions
- Every service has its own ready session.
session-managementhas grouped those sessions and proved an identical code plus submodule snapshot.- Connector type and options are explicit in the config.
- The proxy or load balancer already has a stable URL. Proxy process lifecycle remains outside this MVP; its health and request path are verified here.
Workflow
- Run
scripts/pd_serving.py planwith a PD config and Session Group file. - Review generated commands. Connector options must already be present in each role's vLLM arguments; the controller never invents connector metadata.
- Run
start. Services launch in declared order through the existing single-node Serving entry point. - If any role fails, the controller stops already-started roles in reverse order and returns a failed state.
- Run
statusto inspect every member and the proxy health endpoint. - Run
smoketo send the configured request through the proxy and preserve the response as KV-transfer path evidence. - Run
stop; roles stop in reverse startup order.
Entry point
scripts/pd_serving.py provides plan, start, status, smoke, and stop.
Read only the reference needed for the active phase:
Boundaries
- Single-node start/status/stop belongs to
vllm-ascend-serving. - Session creation, leases, and group teardown belong to
session-management. - A working PD deployment's accuracy or performance belongs to the corresponding validation workflow.
- Hangs, rank divergence, endpoint mismatch, or connector diagnosis after a
stable reproduction belongs to
vllm-ascend-distributed-debug.
What ships with it
6 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.
- 11d ago First seen · 63 lines · 99 tokens per session scan A cc105c29c328
vllm-ascend-pd-serving is a skill published in the GitHub repository maoxx241/vllm-ascend-workspace (36 stars, last pushed 7d ago), licensed MIT. It adds 99 tokens to every session and 639 once invoked, about $0.0005 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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