Getting Started
Ten minutes from install to running, testing, and gating intent. Everything here is deterministic and runs with no AI.
1. Install
npm install -g @skillstech/intentlang
intent help
2. Scaffold a mission
intent init Eligibility
That writes Eligibility.intent, a real starter with a goal, a guarantee, a never
rule, an executable decision, and in-file test cases. It is valid and runnable out of
the box.
3. Run it (no code, no AI)
A decision is a program. Give it inputs and it decides:
intent run Eligibility.intent --inputs '{"age":20}'
# decision Example: Allowed [rule: adult]
The trace shows which rule fired. Change the input and the result changes, deterministically, before any implementation exists.
4. Test it, in the same file
The test blocks assert behavior through the same runtime:
intent test Eligibility.intent
# intent test Eligibility.intent: 2/2 passed
The .intent file is now self-verifying. No test framework, no code.
5. Format it
intent fmt Eligibility.intent --write
Canonical whitespace, comments preserved. Use intent fmt . --check in CI to keep a
whole tree consistent.
6. Check it
intent check Eligibility.intent
Diagnostics for one file, or gate a whole repo at once:
intent check . # recurses every .intent, exits non-zero on any error
Add it to CI with the GitHub Action:
- uses: SkillsTechTalk/intent-language@main
with:
paths: ./intent
7. Edit with intelligence
Install the editor support: the Language Server (intent lsp)
gives live diagnostics, completion, and hover in VS Code, Neovim, and any LSP editor,
plus syntax highlighting via the shipped grammar.
8. Go further
- Executable intent in depth: the Intent Runtime and first-class tests.
- Interop: export to DMN/BPMN/JSON-Schema/OpenAPI and import back.
- The whole language: the syntax overview and the specification.
- The model everyone builds on: Intent for every role.
The whole loop, author, run, test, format, gate, in one deterministic toolchain. That is what beyond prompt engineering looks like in practice.