系统通过 Agent自动盘点线下资源，或者是其他云上面的资源的集群配置、存储容量、计算资源使用情况等元信息，结合阿里云性能基准模型进行资源评估与成本预估。自动生成上云架构建议与资源规划方案，支持一键生成迁移计划，提升决策效率。
I then added a few more personal preferences and suggested tools from my previous failures working with agents in Python: use uv and .venv instead of the base Python installation, use polars instead of pandas for data manipulation, only store secrets/API keys/passwords in .env while ensuring .env is in .gitignore, etc. Most of these constraints don’t tell the agent what to do, but how to do it. In general, adding a rule to my AGENTS.md whenever I encounter a fundamental behavior I don’t like has been very effective. For example, agents love using unnecessary emoji which I hate, so I added a rule:
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IAG reports record operating profits on margins of more than 15% at British Airways and sister airline Iberia