360 Secure SkillHub
360 安全技能中心

agentscope-benchmark-runner

该 Skill 为 AgentScope 2.0 智能体和流水线生成基准场景文件与 Python 运行脚本,支持延迟、吞吐量和提示词/模型对比场景,并输出 JSON/CSV 结果用于复现实验;真实模型运行需配置凭据,生成配置使用占位 API Key。

trend0522
trend0522
热度 7.65
最近更新 2026-10-03 10:11:21
分类:开发依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:代码生成 / 自动化脚本 / 报告撰写

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add agentscope-benchmark-runner
Metadata
name
agentscope-benchmark-runner
description
Run benchmarks against AgentScope 2.0 agents and pipelines. Use this when the user wants to measure latency, throughput, token usage, or compare model/prompt performance in a reproducible way.
version
0.1.0
metadata
{"openclaw":{"requires":{"env":["OPENAI_API_KEY"],"bins":["python3"]},"primaryEnv":"OPENAI_API_KEY","envVars":[{"name":"OPENAI_API_KEY","required":false,"description":"Optional API key for live benchmark runs."},{"name":"AGENTSCOPE_MODEL","required":false,"description":"Optional default model for benchmark configs."}],"emoji":"🏁","homepage":"https://github.com/agentscope-ai/agentscope"}}

AgentScope Benchmark Runner

This skill generates benchmark configs and a runner for AgentScope 2.0 agents. It focuses on reproducible performance measurement for:

  • single-agent latency
  • pipeline throughput
  • token usage estimation
  • prompt variant comparison

What this skill does

  • Creates benchmark scenario files
  • Generates a runner script for repeated measurements
  • Outputs JSON/CSV results for analysis
  • Supports baseline and variant comparisons

How to use

Run the generator script from this skill folder:

python3 scripts/generate_benchmark.py --output /path/to/benchmarks --scenario latency

Supported scenarios:

  • latency - single request latency benchmark
  • throughput - concurrent request throughput benchmark
  • compare - prompt/model variant comparison

After generation:

cd /path/to/benchmarks
python run_benchmark.py

Security notes

  • Generated configs use placeholder API keys
  • No secrets are hardcoded in benchmark files
  • Results files may contain prompt text; review before sharing

Troubleshooting

  • If agentscope import fails, install the package: pip install agentscope
  • For model-specific benchmarks, configure the provider credentials
  • High concurrency benchmarks may hit rate limits; adjust --concurrency