easy_vllm_simulator: Skill for Claude Code

.claude/skills/adversarial-benchmark/SKILL.md

adversarial-benchmark is a skill for Claude Code from tbvjvsladla/easy_vllm_simulator. It costs 271 tokens per session (8,343 once invoked), scanned A, original, no licence file.

A performance-testing guide for an active vLLM server, which serves machine-learning models and generates their responses.

In plain words
What is it for?
Use it to benchmark model serving, investigate slow response generation, or run a performance gate before accepting a serving setup.
Why use it?
It challenges claims that the server is fast enough and can reject performance that falls below the expected standard.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is tbvjvsladla/easy_vllm_simulator's own configuration. It tells Claude Code how to work on easy_vllm_simulator itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything easy_vllm_simulator configures →

Reuse

Borrowing it

Nothing to install: this file belongs to tbvjvsladla/easy_vllm_simulator. 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/tbvjvsladla/easy_vllm_simulator/single-node/.claude/skills/adversarial-benchmark/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/tbvjvsladla/easy_vllm_simulator

Made for: Claude Code.

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.

agentmods badge for adversarial-benchmark

README.md
[![agentmods](https://agentmods.dev/badge/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark/github.svg)](https://agentmods.dev/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark)
Your own site
<a href="https://agentmods.dev/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark"><img src="https://agentmods.dev/badge/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark/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.

agentmods 80×15 button for adversarial-benchmark

Your own site · 80×15
<a href="https://agentmods.dev/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark"><img src="https://agentmods.dev/badge/skills/tbvjvsladla/easy_vllm_simulator/adversarial-benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 271 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,343 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00271 $0.08343
Opus 5 $0.00135 $0.04172
Sonnet 5 $0.00054 $0.01669
Haiku 4.5 $0.00027 $0.00834

Measured 4d ago against content hash 4d415d3ffefb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

adversarial-benchmark scanned grade A 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.

The scan reads SKILL.md. This mod also ships 22 executable files (scripts/broad_search.sh, scripts/classify_cell.py, scripts/conformance_full_superset_lite.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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| 승격 게이트 | 성능 판정 `verdict == PASS`(미달 시 `perf_waiver`) | **서빙 성립(기능)** = 모델이 실제로 떠서 curl 통신으로 응답을 낸다 **∧ 유효 측정**(`floor > 0` ∧ `ratio ≠ null`) |
.claude/skills/adversarial-benchmark/SKILL.md · 190 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

33 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.

  1. 4d ago Changed · +9 lines 4d415d3ffefb
  2. 5d ago Changed 12277e229a06
  3. 10d ago First seen · 181 lines · 271 tokens per session scan A 7af2a68769fa

Subscribe to this mod's changes

adversarial-benchmark is a skill published in the GitHub repository tbvjvsladla/easy_vllm_simulator (20 stars, last pushed yesterday), with no licence file. It adds 271 tokens to every session and 8,343 once invoked, about $0.0014 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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