Content preflight

The agent prompt

Copy this brief into your coding agent from the root of the project you want to build in. It names the behaviour, the constraints, and the checks to run — the decisions Jev makes stay explicit so you can see what the model actually decided.

Build a "Content preflight" tool in this repository using Jev from TypeSafe AI.

Inspect the project and use its existing framework, styling, and package manager. Follow the official TypeSafe skill; install it with npx skills add typesafe-ai/skills --skill typesafe-ai only if needed.

The user pastes a short post or ad draft. Evaluate independent dimensions in one call: Noul questions for a clear hook, a concrete claim, and a specific call to action; a Score for clarity using three explicit rubric levels; and a Choice for dominant tone (educational, conversational, provocative, promotional). Combine the dimensions in ordinary code into a transparent preflight checklist—never a vague single "quality" score. Let users edit the draft and compare the latest result with the previous one.

Requirements:
- Keep TYPESAFE_API_KEY server-side and use the official SDK.
- Label every result as a model judgment, not a guarantee of performance.
- Show values, confidence, and probabilities; flag low confidence.
- Keep comparison history local to the browser and provide a clear reset.
- Add mocked integration tests and tests for the composite display logic.
- Document the question rubrics and setup.

Run all relevant checks and report what changed.

Built something like this

Community projects in the directory that solve a similar problem:

• SuperX post scoring
• Draftpulse
• jev-ad-preflight