alt Hacker NewsThere are many other posts here which agree with you. Filling context with what you think the model needs adds nothing and possibly just inflates context which is harmful.
A good method seems to be only make a skill or memory when the LLM gets something wrong, or if you actually observe it's always doing the same step and you can get the model to the same place with less tokens.
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> Filling context with what you think the model needs adds nothing and possibly just inflates context which is harmful.
The solution that I've developed is, let the agent figure things out efficiently, without inflating the context. I have what I call a smart repo that better explains this at
https://github.com/gitsense/smart-ripgrep
The basic idea is, when the agent does a ripgrep it gets back files + matching lines + context.
I’ve basically never edited a skill or memory myself. I make the LLM do it as part of the /handoff skill before I clear a session. That also includes pruning existing skills/memories and resolving any drift.
Even the /handoff skill was written by the model…