Are we sure that unrestricted free-form Markdown content is the best configuration format for this kind of thing? I know there is a YAML frontmatter component to this, but doesn't the free-form nature of the "body" part of these configuration files lead to an inevitably unverifiable process? I would like my agents to be inherently evaluable, and free-text instructions do not lend themselves easily to systematic evaluation.
Then rename your markdown skill files to skills.md.yaml.
There you go, you're welcome.
The modern state of the art is inherently not verifiable. Which way you give it input is really secondary to that fact. When you don't see weights or know anything else about the system, any idea of verifiability is an illusion.
>doesn't the free-form nature of the "body" part of these configuration files lead to an inevitably unverifiable process?
The non-deterministic statistical nature of LLMs means it's inherently an "inevitably unverifiable process" to begin with, even if you pass it some type-checked, linted, skills file or prompt format.
Besides, YAML or JSON or XML or free-form text, for the LLM it's just tokens.
At best you could parse the more structured docs with external tools more easily, but that's about it, not much difference when it comes to their LLM consumption.