Four offline checks before giving a marketing agent API access

说明与用途

四个离线工具在将营销代理连接到实时账户之前，帮助发现常见错误。每个工具使用合成数据验证 CPA 计算、价格与套餐差异、CRM 覆盖率和本地邮件资格检查。

问题

Marketing agents can misinterpret data and make wrong decisions even when producing valid JSON. The goal is to expose such errors before connecting an agent to a live account.

结果

The four tools collectively demonstrate how to detect common agent misinterpretations—incorrect CPA calculation, price versus package changes, incomplete CRM reads, and local eligibility checks—without accessing live data.

工作流

• Download and unpack each tool’s ZIP file from GitHub releases.
• Run the provided Python command for each tool with the synthetic example data.
• Observe the command’s exit code and output values.
• Compare the observed values with the expected results described in the article.
• Report any mismatches and explain unsupported conclusions the agent might make.
• Do not connect to live accounts or perform any real data operations.
• Use the results to refine agent prompts or workflows before live deployment.

证据

Each has synthetic input and a result you can reproduce with Python 3.9+ and the standard library.

来源

The fictional input contains five rows and four grouped placements. The result has 97 clicks, 6,000 RUB cost and 5 conversions. Total CPA is 1,200.00 RUB.

来源

In the synthetic strategy-session package, the price changes from 10,000 to 12,500 RUB: +25%. Delivery changes from four to six business days, and interview quantity changes from two to one.

来源

Deal 101 has the complete empty read. Deal 105 has incomplete coverage: its absence status cannot be established.

来源

The six invented rows produce one eligible-under-supplied-rules row and five excluded rows.

来源