The standardization is for presentation of how the information is made available to the harness. Optimizations in how the information is presented to the model can be iterated on without impacting the presentation to the harness. Initially, agent skills have already been provided by:

(1) providing a bash tool with direct access to the filesystem storing the skills to the model,

(2) providing read_file and related tools to the model,

(3) by providing specialized tools to access skills to the model,

(4) by processing the filesystem structure and providing a structure that includes the full content of the skills up front to the model.

And probably some other ways or hybrids.

> It increases benchmarks a few points now but what's the point in standardizing all this if it'll be obsolete next year?

Standardizing the information presentation of skills to LLM harnesses lets the harnesses incorporate findings on optimization (which may be specific to models, or at least model features like context size, and use cases) and existing skills getting the benefit of that for free.