skillscript

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?