RU version is available. Content is displayed in original English for accuracy.
The itch started with something small. I wanted my NanoClaw agent to run my morning brief the same way every day. Check overnight tickets, summarize the deploy pipeline, flag anything urgent. Every session, it would re-figure out how to do this from scratch, drift a little, and cost tokens for what's basically a fixed procedure. I could put it in a system prompt or an MD skill file, but those are still instructions the model reads and reasons about every time. And I wanted it to run autonomously and then hand it to the model to reason over the data.
The second thing that pushed me: I wanted to use small local models for the cheap stuff. They're capable, but if you just hand them the wheel, they wander. What I wanted was a way for the frontier model (or me) to write a specific procedure and hand it to the local model to execute, not interpret. The skillscript is the program; the model is the runtime.
Skillscript is that. A skillscript is a text file with named steps, variables, conditions, and calls out to tools (MCP connectors, a local model, and shell commands from an operator allowlist). It's deliberately minimal — no eval, no arbitrary imports, no subprocess, no unbounded loops. Bounded language, limited potential for damage. Everything a skillscript can do is in the file. You read it and know.
Where it is: pre-1.0 (0.30), MCP-native, self-hosted. Rough edges I know about: first-run setup takes more steps than it should, some of the grammar is still moving, and the local model integration currently assumes Ollama. It works well enough that I use it every day, but I wouldn't necessarily call it production-ready.
- Repo: [https://github.com/sshwarts/skillscript](https://github.com/sshwarts/skillscript)
- Site: [https://skillscript.ai](https://skillscript.ai)
- Docs: [https://skillscript.mintlify.app/docs](https://skillscript.mintlify.app/docs)
- npm: `skillscript-runtime`
I'd welcome critique on two things especially: the language design (is it too small? too big? wrong shape?) and the trust model around agent-authored skills. What would you want to see before you trusted this on your own machine?
Discussion (9 Comments)Read Original on HackerNews
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.