Models work best when they have short instructions and no noise. "Conversation [may] contain" also means "conversation has a lot of noise". It degrades performance and increases cost.
I use handoff skill to ask model to write a prompt for itself.
Models work best when they have short instructions and no noise. "Conversation [may] contain" also means "conversation has a lot of noise". It degrades performance and increases cost.
I use handoff skill to ask model to write a prompt for itself.
The applicability of your advice is very model dependent. Some like Claude have very good long context performance, whereas others they fall off much quicker past some threshold.
You're right that it's model dependent, even within Claude models.
I've found Opus 5 far better as a subagent with very limited context window use, which could suggest that it might not have good long context performance unlike its predecessors. (I was one of many tearing my hair out trying to work with Opus 5 for the past week.)
I am not only talking about "long context" performance (context rot), but also about noise that is confusing model about its goal (from correctly extracting operator's intent). I think every model will get confused to a degree, so clearing up irrelevant information from context helps a lot.