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Download the free Jev_System_One_Reference.md file from the public GitHub repository, put it in your project workspace, and explicitly ask your coding assistant to read it before it writes Jev integration code. Jev is not the model that powers Claude Code, Codex, or Cursor: it returns structured decisions, while your coding assistant remains responsible for writing and editing code.
Get the free Jev reference file into your project
- Open the Jev System One Reference repository and download
Jev_System_One_Reference.md. - Place the Markdown file in the project folder that your coding assistant can access. You can also provide the file directly through the assistant’s file-attachment or workspace features.
- Ask the assistant to read the actual file, starting with Section 0, before proposing an implementation. Naming the file or sharing a URL alone does not establish that the assistant has read its contents.
- Give it a concise project brief and any relevant existing files. Ask for a small implementation, a way to verify it, and an updated handover that distinguishes completed work from plans and records checks it could not run.
The repository is an independent reference document, not an official TypeSafe publication, application, SDK, or deployed service. Its README accompanies reference edition 1.1.1, prepared September 22, 2026 from a source snapshot compiled September 20, 2026.
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Try a small project with Claude Code, Codex, or Cursor
For a first exercise, ask your coding assistant to build a support-ticket router that uses Jev to classify tickets. A useful prompt gives the assistant both the reference file and concrete implementation constraints:
Read Jev_System_One_Reference.md, starting with Section 0. Build a small support-ticket router that uses Jev to classify incoming tickets. Include a mock mode that works without an API key. Read credentials from environment variables; do not put secrets in source code. Implement the project, run the checks available in this workspace, and provide a handover that separates completed work from anything planned or not verified.Treat the result as generated integration code, not proof that a live Jev request succeeded. In particular, a mock response can help exercise application logic but cannot show that Jev classified real tickets accurately. The reference’s sample response is hand-authored, its proposed acceptance checks are not completed tests, and the example does not establish server acceptance or a live integration.
Understand Jev’s role in the workflow
TypeSafe describes Jev as a typed-decision model. An application supplies a state and fixed-form questions; Jev returns structured answers such as a choice among options, a rubric score, or a noul value for a true-or-false statement. The application’s code must validate those results and decide what to do with them.
Jev does not generate prose or code, carry on a conversation, call tools, or edit project files. Those remain jobs for a coding assistant’s language model and the application around Jev. TypeSafe puts the distinction plainly: “Jev is not a drop-in replacement for the LLM behind Claude Code, Cursor, opencode, Copilot, Muse Spark, Grok Bot, or similar tools.”
Choose the route that matches what you want to do
| Your goal | Suitable route | What it does |
|---|---|---|
| Help a coding assistant write Jev integration code | Provide the independent Markdown reference, or install TypeSafe’s official skill | The reference supplies documentation as context; the official skill is TypeSafe’s agent-oriented guidance. |
| Use Jev in a product or agent you are building | Call Jev from your application or agent code | Your code sends the decision request, validates the structured response, and controls any resulting action. |
| Try Jev before building an integration | Use TypeSafe’s Jev playground | Explore the model separately from a coding-agent workflow. |
| Make Jev the model that writes code in your editor | No supported path is described by TypeSafe | Jev is a decision model, not a replacement for the editor’s code-generating language model. |
These options are not interchangeable: a reference file gives an assistant context, a skill supplies agent guidance, and a live API call lets software request Jev decisions.
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Install TypeSafe’s official agent skill instead
If you want TypeSafe’s own guidance available to your agent, its official agent-skill documentation lists these installation commands:
Claude Code
claude plugin marketplace add typesafe-ai/skills
claude plugin install typesafe@typesafe-aiOther supported agents
npx skills add typesafe-ai/skills --skill typesafe-aiSelect your agent when prompted. Installation is project-local by default; add -g to make it global. Installer behavior and agent support can change, so check TypeSafe’s current instructions if the commands or prompts differ.
Keep examples and reported results in perspective
The independent reference README summarizes a Browser Use project report of 7.1 seconds for a Google Flights task, involving 17 Jev requests and 178 ms median latency. The reference author says this result was not reproduced there and is not a general reliability benchmark. It should not be read as a performance expectation for your project.
A separate article by Sebastian Bennis reports one request containing seven questions completing in 0.62 seconds at an approximate cost of $0.00005. That is an author-reported single test, not a general latency or cost guarantee. The article also quotes pricing of $0.042 per million input tokens with output free; treat that as the price reported by the article in 2026, and consult TypeSafe’s official site for current pricing before building around it.
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Examples, mock fixtures, and individual reports can help explain a workflow, but they do not establish that a request will be accepted, that a particular editor has a working live integration, or that a model’s decisions are accurate for your use case. Verify each of those in the application you build.
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Frequently Asked Questions
Can I select Jev as a model in Cursor or Claude Code?
No supported option is documented for using Jev as the code-generating model in those editors. Jev returns structured decisions; the editor’s language model writes and edits code.
Does Jev work with Claude Code?
Claude Code can help you build code that calls Jev if you provide the reference file or use TypeSafe’s official skill. That does not mean Jev powers Claude Code’s own coding model.
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