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 skills add AgenticAIPlan/AgenticAISkills --skill benchmark-model-testgit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote 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/agenticaiplan/agenticaiskills/benchmark-model-test)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/benchmark-model-test"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/benchmark-model-test.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 5.1 | $0.00058 | $0.01130 |
| Opus 5 | $0.00029 | $0.00565 |
| Sonnet 5 | $0.00012 | $0.00226 |
| Haiku 4.5 | $0.00006 | $0.00113 |
Grade A, and why
benchmark-model-test 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 8d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Model Test
自动化测试多个大模型的响应，对比输出质量，并将结果保存到 Excel 表格中。
适用场景
当用户需要：
- 批量测试多个模型对同一组 prompt 的响应
- 对比不同大模型的输出质量
- 自动化收集模型测试数据
- 进行 benchmark 测试或模型评估
触发条件：用户提到 "benchmark"、"模型测试"、"模型对比"、"批量测试" 等关键词。
输入要求
Excel 文件
| 列 | 内容 | 说明 |
|---|---|---|
| D (索引3) | prompt | 测试输入文本，必需 |
| G (索引6) | other | 附件文件名，用 / 分隔多个文件，可选 |
| H+ (索引7+) | 模型名称 | 表头填写模型名，数据行保存响应结果 |
表头示例：
| A | B | C | D | E | F | G | H | I | J |
|---|---|---|---|---|---|---|---|---|---|
| 序号 | 任务 | 描述 | prompt | 状态 | 备注 | other | ERNIE-5.0-Thinking | gpt-5.4 | claude-sonnet-4.5 |
附件文件（可选）
- 存放在
other/文件夹中 - 支持图片格式：jpg、jpeg、png、gif、webp
- 支持文档格式：txt、pdf、doc、docx、csv、xlsx、xls
执行步骤
- 获取配置：询问用户模型平台地址
- 读取配置：从 Excel 表头 H 列起读取要测试的模型名称
- 模型匹配：根据关键字匹配平台上可用的模型
- 启动浏览器：打开用户指定的模型平台页面
- 检查登录：如需登录，等待用户手动完成
- 逐行测试：
- 创建新对话
- 选择模型
- 上传附件（如有）
- 输入 prompt 并发送
- 等待响应完成（15秒稳定性检测）
- 保存结果到对应列
- 自动保存：每个模型测试完成后立即保存 Excel
输出要求
Excel 结果
- 模型响应保存在表头对应的列中
- 响应内容完整，无截断
- 错误信息以
错误:前缀保存
测试日志
- 显示当前处理行和模型
- 显示响应时间和字符数
- 显示保存位置
支持的模型
| 模型名称 | 描述 |
|---|---|
| ERNIE-5.0-Thinking | 免费创意写作效果好 |
| ERNIE-4.5-Turbo | 免费速度快 |
| seedance-1.5-pro | 音画同步视频生成 |
| seed-2.0 | 免费多模态理解 |
| gpt-5.4 | OpenAI新作 |
| GPT-5.2 | 全能助手 |
| GPT-5.1 | 日常对话 |
| nano-banana-2 | 图像生成 |
| gemini-3-pro-preview | 多模态理解 |
| nano-banana-pro | 图像理解 |
| claude-opus-4.6 | 代码分析 |
| claude-sonnet-4.5 | 长文本分析 |
| DeepSeek-V3.2 | 免费快速通用 |
| Qwen3-235B-Thinking | 免费推理数学 |
使用方式
node scripts/skill.js --file benchmark.xlsx
node scripts/skill.js --file benchmark.xlsx --auto
node scripts/skill.js --file benchmark.xlsx --start-row 2 --timeout 480
参数说明
| 参数 | 说明 |
|---|---|
-f, --file |
Excel 文件路径 |
-s, --start-row |
开始行号（默认 2） |
-t, --timeout |
单个模型最长等待时间，秒（默认 480） |
--auto |
自动模式，跳过交互确认 |
依赖安装
npm install playwright xlsx
npx playwright install chromium
注意事项
- 运行时需要用户输入模型平台地址
- 首次使用需手动登录
- Thinking 模型响应时间较长
- 表头模型名称支持关键字匹配
- 自动模式下需通过环境变量
PLATFORM_URL指定平台地址
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.
- 8d ago First seen · 125 lines · 58 tokens per session scan A 44c47a3bccc8
benchmark-model-test is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 58 tokens to every session and 1,130 once invoked, about $0.0003 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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