1. How a this better than just using any other script language?
2. Inventing a new language complicates large models ability to generate such scrips compared to a well-known language. Did you find it to be a problem? How did you mitigate?
3. The AI is showing. :) I had the similar discussion with ChapGPT and some phrasing is near the same. Not a dig, just a funny observation.
4. Consider the recursive nature of the problem you’re solving - large model updates workflow which you review each time, worker models generate plans and tool calls which you don’t review. A constrained language is useful in both cases to guide the model.
5. This Earlier discussion can provide useful background for why this is needed. You have probably seen it, but the readers will likely appreciate. https://news.ycombinator.com/item?id=48051562
The problem is real, Thank you for taking a stab and sharing your findings.
I really appreciate the comments and the encouragement.
"How <is> this better than just using any other script language?"
I wanted to make the language something built for a machine to write and a human to approve with a narrow scope and my control of what extends that. What shell commands, if any. What MCP and what tools in that MCP, and so on. If an agent generates a Python script to run unattended every morning, I feel I can't control it.
"Inventing a new language complicates large models ability to generate such scripts..."
I tried to keep it as small as possible and borrow a lot from what I knew models had seen in makefiles, YAML-ish, etc.
That was actually the question I began with. What would a make file look like if I were using it to make a classic markdown skill? Asking that question, sort of spawned the rest of it.
I tested the language against cold agents in both frontier model and local model camps to see where they had difficulty nad made changes as required. The lint approach as well as help topics from the MCP helped a lot.
"AI Showing..."
Yea there is a certain irony there. I freely admit product was written with Claude Code. I wrote the Product Requirements & Engineering Requirements and reviewed the code, so I can say I own it.
"Consider the recursive nature of the problem you’re solving..."
That framing is better than mine. When a frontier model writes a skillscript, there's not much chance of something slipping by. Over time, I've become cautiously open to the model adapting the skillscript to solve problems as they occur. Example, a skillscript runs every morning and checks github for PRs and issues. The agent when woken after the run 'noticed' an issue, fixed the script and it was ready for me to approve in the morning. Yes, that could have been done in Python, but I'd not be as confident about it.
It seems like you’re dramatically overcomplicating what could be a 2 bash scripts and a single LLM call. Natural language and LLMs are great for searching the problem space to find a solution, once you find the solution, shrink the stochastic parts (the MD saying “check GitHub” or whatever) and grow the deterministic parts (a bash script) as much as possible.
That's a fair comment. I sorta feel you're describing my thesis, "shrink the stochastic, grow the deterministic" is the point. Where we differ, maybe, is what the deterministic part is made of.
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.
1. How a this better than just using any other script language?
2. Inventing a new language complicates large models ability to generate such scrips compared to a well-known language. Did you find it to be a problem? How did you mitigate?
3. The AI is showing. :) I had the similar discussion with ChapGPT and some phrasing is near the same. Not a dig, just a funny observation.
4. Consider the recursive nature of the problem you’re solving - large model updates workflow which you review each time, worker models generate plans and tool calls which you don’t review. A constrained language is useful in both cases to guide the model.
5. This Earlier discussion can provide useful background for why this is needed. You have probably seen it, but the readers will likely appreciate. https://news.ycombinator.com/item?id=48051562
The problem is real, Thank you for taking a stab and sharing your findings.
I really appreciate the comments and the encouragement.
"How <is> this better than just using any other script language?"
I wanted to make the language something built for a machine to write and a human to approve with a narrow scope and my control of what extends that. What shell commands, if any. What MCP and what tools in that MCP, and so on. If an agent generates a Python script to run unattended every morning, I feel I can't control it.
"Inventing a new language complicates large models ability to generate such scripts..."
I tried to keep it as small as possible and borrow a lot from what I knew models had seen in makefiles, YAML-ish, etc.
That was actually the question I began with. What would a make file look like if I were using it to make a classic markdown skill? Asking that question, sort of spawned the rest of it.
I tested the language against cold agents in both frontier model and local model camps to see where they had difficulty nad made changes as required. The lint approach as well as help topics from the MCP helped a lot.
"AI Showing..."
Yea there is a certain irony there. I freely admit product was written with Claude Code. I wrote the Product Requirements & Engineering Requirements and reviewed the code, so I can say I own it.
"Consider the recursive nature of the problem you’re solving..."
That framing is better than mine. When a frontier model writes a skillscript, there's not much chance of something slipping by. Over time, I've become cautiously open to the model adapting the skillscript to solve problems as they occur. Example, a skillscript runs every morning and checks github for PRs and issues. The agent when woken after the run 'noticed' an issue, fixed the script and it was ready for me to approve in the morning. Yes, that could have been done in Python, but I'd not be as confident about it.
I also really appreciate the link.
It seems like you’re dramatically overcomplicating what could be a 2 bash scripts and a single LLM call. Natural language and LLMs are great for searching the problem space to find a solution, once you find the solution, shrink the stochastic parts (the MD saying “check GitHub” or whatever) and grow the deterministic parts (a bash script) as much as possible.
That's a fair comment. I sorta feel you're describing my thesis, "shrink the stochastic, grow the deterministic" is the point. Where we differ, maybe, is what the deterministic part is made of.
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.
In Brave, on stock Google Pixel 10, guard enabled, docs site layout is broken.
Thanks. I'm guessing since the docs are mintlify hosted, the CDN assets might be being blocked. I'll look and see if adding a domain sidesteps it.
same, Zen Browser (Firefox fork) on Linux
Is what you are seeing is the topics sidebar overlapping the text?