I run evals and the Todo tool doesn't help most of the time. Usually models on high thinking would maintain Todo/state in their thinking tokens. What Todo helps is for cases like Anthropic models to run more parallel tool calls. If there is a Todo list call, then some of the actions after are more efficient.
What you need to do is to match the distribution of how the models were RL-ed. So you are right to say that "do X in 200 lines" is a very small part of the job to be done.
What you need to do is to match the distribution of how the models were RL-ed. So you are right to say that "do X in 200 lines" is a very small part of the job to be done.