Abid Ali Awan writes a tutorial showing how to wrap existing Python functions as tools for an LLM agent using the OpenAI Agents SDK. The process involves decorating a function with `@function_tool`, defining an `Agent` with instructions and a tools list, and letting the `Runner` manage the loop where the model decides which tools to call, what arguments to pass, and when to stop. The example uses a simple website-latency checker that becomes an agent capable of comparing response times across multiple URLs and explaining results in natural language.
- The SDK auto-generates the JSON tool schema from the function signature and docstring; no manual schema is needed.
- The same pattern applies to CSV analysis, server monitoring, log analysis, and API automation.
- Cheaper models such as GPT-5.6 Luna make multi-agent tool-calling systems more affordable at scale.
- The SDK auto-generates the JSON tool schema from the function signature and docstring; no manual schema is needed.
- The same pattern applies to CSV analysis, server monitoring, log analysis, and API automation.
- Cheaper models such as GPT-5.6 Luna make multi-agent tool-calling systems more affordable at scale.
