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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteJev does not replace the model that writes code in Claude Code, Codex, or Cursor. It returns structured decisions—such as a choice, score, or true/false answer—that an application can use. To help a coding assistant build a Jev integration, download the free Jev_System_One_Reference.md file, make its contents available in your project, and explicitly ask the assistant to read it before it starts.
Get the free Jev reference file
The reference is a Markdown document in an independent public GitHub repository, not an application, SDK, or deployed service. Download Jev_System_One_Reference.md from the Jev System One Reference repository and put it in the project folder where your coding assistant can access it.
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The repository README accompanies reference edition 1.1.1, prepared September 22, 2026, from a source snapshot compiled September 20, 2026. It identifies the document as an independent reference, not an official TypeSafe publication. Those edition dates describe this reference file; they do not establish the current Jev API or model version.
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- Make the actual file available. Save it in the project workspace or provide the Markdown contents directly. A URL or filename by itself does not show that the assistant has read the material.
- Ask it to read Section 0 first. Then give it a specific project brief and any relevant project files. For a first exercise, request a small support-ticket router that calls Jev for a decision.
- Set implementation boundaries. Ask for a mock mode that works without an API key, and require credentials to come from environment variables rather than being embedded in source code.
- Request verification and a handover. Ask the assistant to implement the integration, run the checks it can, and report which checks passed and which could not be run. Keep completed work distinct from planned work.
These steps apply whether you are working in Claude Code, Codex, or Cursor: the coding assistant uses the document as context while producing code. The reference repository describes a workflow; it does not prove that a particular editor has been tested end to end.
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What Jev does in an integration
TypeSafe describes Jev as a typed-decision model. An application supplies a state and fixed-form questions; Jev returns structured results such as a choice among options, a rubric score, or a noul value representing a true/false statement. The application then validates the result and decides what to do with it.
That makes Jev suitable for bounded decisions inside an app or agent—for example, classifying or routing a support ticket—while the coding LLM remains responsible for writing and editing code. TypeSafe puts it plainly: “Jev is not a drop-in replacement for the LLM behind Claude Code, Cursor, opencode, Copilot, Muse Spark, Grok Bot, or similar tools.” See TypeSafe’s official Jev with coding agents documentation.
Choose the path that matches your goal
| Goal | Path | What it means |
|---|---|---|
| Help a coding assistant write Jev integration code | Provide the independent reference file, or install TypeSafe’s official skill | The reference supplies documentation context; the official skill is TypeSafe’s agent guidance. They are not the same resource. |
| Use Jev in a product or agent | Call Jev from the application or agent code | Your application validates Jev’s structured response and determines the resulting action. |
| Try Jev before building | Use TypeSafe’s playground | This is a way to explore Jev, not a way to make it the coding editor’s writing model. |
| Replace the coding agent’s model with Jev | No supported path is described in TypeSafe’s documentation | Jev does not generate text, hold a conversation, call editor tools, or edit project files. |
TypeSafe’s official agent-skill page documents two Claude Code plugin commands: claude plugin marketplace add typesafe-ai/skills and claude plugin install typesafe@typesafe-ai. For other supported agents, it documents npx skills add typesafe-ai/skills --skill typesafe-ai; select the agent when prompted. Installation is project-local by default, while -g makes it global. These commands and compatibility details were current as checked October 7, 2026; agent installers and client support can change.
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What examples do—and do not—prove
The reference repository includes an illustrative support-ticket response, proposed acceptance checks, and example request and test materials. Its README says the response is hand-authored and the proposed checks are not completed tests. A mock result does not establish Jev’s classification accuracy, server acceptance, or a live integration.
Performance figures in the related material have different sources and scopes, so they should not be treated as guarantees. Sebastian Bennis reported one request with seven questions taking 0.62 seconds and costing about $0.00005 in 2026. Separately, the reference README summarizes a Browser Use project report of 7.1 seconds for a Google Flights task, 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.
Bennis’s September 24, 2026 article also quoted a Jev price of $0.042 per million input tokens with output free. That is an article-reported price, not a current-price guarantee; check TypeSafe’s current official pricing before relying on it.
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Does Jev work with Claude Code, Codex, or Cursor?
Yes, in the sense that a coding assistant can use the reference or supported agent guidance to help build code that calls Jev. No, if you mean selecting Jev as the model that writes code inside the editor: TypeSafe’s documented distinction is that Jev supplies structured decisions, while the coding agent’s LLM writes and edits the project. The exact integration options depend on the current agent and TypeSafe documentation.
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