The problem I'm trying to solve for me is a step removed. The agent is the one writing the script, and I want it to run unattended against my systems every morning. I can't let it write and run bash. Even though my agent lives in a container (NanoClaw), I still need it to reach out to other systems. Github, my other servers, MCPs, etc.
Skillscript is how I let it reach out without holding the keys. It can invoke a skillscript that hits GitHub, but it never runs the raw command or holds the token itself. The runtime holds the credential and only lets it through the skillscript I approved.
It's fair to say a skillscript basically is your two bash scripts and an LLM call, but fenced in.
What about skillscript is unique that couldn't be done with bash or python as a permissioned tool? (Trying to understand where you see the difference.)
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My original impression from the repo was that the language/toolkit is overengineered, but then I saw on the website that the intention is for the agents to write their own tools. That helps explain some of the complexity.
I think the rest of the perceived complexity is the over-explaining in the README.
I don't think anyone's going to really engage with all of that so you might have better luck chopping it down 80% to only highlight the stuff that matters.
I think you're right on. I let the readme get out of hand. It became a README, changelog mash-up. Going to rewrite it, and the 80% metric is a good one. Is there an example of what you consider the perfect readme?
Re: README -- I can't recall a specific repo with one off the top of my head so took a stab at editing yours[1] instead of hunting around. It's not perfect -- I'd want to trim the bullet lists further, for example -- but is much more scannable in my opinion.
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[1] https://gist.github.com/thedatadavis/fbbe556348eb43731659456...