Playbill Fact Gate
Paste program copy and a verified production fact sheet; Jev independently checks names, credits, and dates against the source, and code holds any item that fails verification.
Noul Check· yes/no probability
Section · Jev
full primer →The kernel.
Jev answers a short checklist of yes/no questions about Production communications for directors, each as a probability, and simple rules turn them into pass, review or fail.
Why this primitiveTyped verification decisions reduce factual errors without having a model rewrite publication copy.
Kernel
several independent Jev `noul` questions (one per condition) asked together over the same state, combined by explicit code rules
Drives the UI as
a checklist of conditions, each with a 0-1 probability meter and a pass / review / fail colour from code-owned thresholds
Required key.
TYPESAFE_API_KEY
Your TypeSafe key. The mega-prompt asks for it with a secure form and keeps it on the server. Jev returns typed decisions: choice, noul (yes/no probability) and score.
open ↗Add this in your Lovable project under Settings → Secrets before pasting the prompt below.
Appendix · Mega-prompt
The build prompt.
budget · 1 message
Paste into a fresh Lovable project. Make sure the key above is set first. read the build strategy →
Build "Playbill Fact Gate" as a ONE-SHOT Lovable build (~5 credits, no follow-ups).
Single-page TanStack Start app, one route, cut scope ruthlessly.
THIS PROMPT IS SELF-CONTAINED
Do not assume the participant knows Jev or has read any other page. TypeSafe Jev is a decision model,
not a text generator. It receives `state` plus a map of typed `questions` and returns JSON that code can
use directly. Use Choice to select exactly one defined option, Noul for a yes/no probability from 0 to 1,
and Score for a probability-weighted position across ordered levels. Keep rules, thresholds, arithmetic,
and actions in code. Use a generative model only if the product separately needs prose.
CONCEPT
Paste program copy and a verified production fact sheet; Jev independently checks names, credits, and dates against the source, and code holds any item that fails verification.
Discipline: Theater & Live Performance (Production communications).
Jev pattern: Noul Check (yes/no probability) — several independent Jev `noul` questions (one per condition) asked together over the same state, combined by explicit code rules.
Why typed decisions: Typed verification decisions reduce factual errors without having a model rewrite publication copy.
ENGINE: TypeSafe Jev (typed decisions, not text)
- Before writing code, ask the participant for `TYPESAFE_API_KEY` with Lovable's secure secret form. Never
ask them to paste it into chat, never prefix it with `VITE_`, and never expose it to browser code.
- Put the callable server function in `src/lib/jev.functions.ts`; do not import a server-only module from UI code.
- Validate the user's input before the handler and read `process.env['TYPESAFE_API_KEY']` inside the handler.
- From the server, call:
POST https://api.typesafe.ai/v1/systemone
Authorization: Bearer <TYPESAFE_API_KEY>, Content-Type: application/json
body: { "model": "jev-latest", "state": <Playbill draft alongside verified names, credits, and dates>, "questions": QUESTIONS }
- Ask all questions in ONE request (they run in parallel and cannot see each other).
- Read Choice from `answers[id].choice`, `.probabilities`, and `.confidence`; Score from `.score`,
`.probabilities`, `.legend`, and `.confidence`; Noul from `.noul` only (it has no separate confidence).
SERVER IMPLEMENTATION (adapt the input name and result mapping to this concept)
```ts
import { createServerFn } from "@tanstack/react-start";
import { z } from "zod";
const Input = z.object({ text: z.string().trim().min(1).max(20000) });
export const decide = createServerFn({ method: "POST" })
.inputValidator((input: unknown) => Input.parse(input))
.handler(async ({ data }) => {
const apiKey = process.env['TYPESAFE_API_KEY'];
if (!apiKey) return { ok: false as const, status: 500, message: "TYPESAFE_API_KEY is not configured." };
const requestBody = {
model: "jev-latest",
state: { text: data.text },
questions: QUESTIONS,
};
let response: Response | undefined;
for (let attempt = 0; attempt < 3; attempt += 1) {
response = await fetch("https://api.typesafe.ai/v1/systemone", {
method: "POST",
headers: { Authorization: `Bearer ${apiKey}`, "Content-Type": "application/json" },
body: JSON.stringify(requestBody),
});
if (response.ok || (response.status !== 429 && response.status < 500)) break;
if (attempt < 2) await new Promise((resolve) => setTimeout(resolve, 750 * 2 ** attempt));
}
if (!response) return { ok: false as const, status: 503, message: "Jev did not respond." };
if (!response.ok) {
const message = (await response.text()).slice(0, 500) || `Jev request failed (${response.status}).`;
return { ok: false as const, status: response.status, message };
}
const result = await response.json();
return { ok: true as const, answers: result.answers };
});
```
In the page component, call `decide` with `useServerFn`, preserve the participant's input while loading or
on error, disable duplicate submissions, and render the returned typed values rather than parsing prose.
QUESTIONS (start here, refine wording if needed)
{
"name_matches": {
"type": "noul",
"instructions": "Do all names in the copy match the verified fact sheet?",
"criteria": {
"true": "At least one name does not match or is not verified.",
"false": "Names match the supplied fact sheet."
}
},
"credit_matches": {
"type": "noul",
"instructions": "Do the stated production credits match the verified record?",
"criteria": {
"true": "A credit conflicts with or is absent from the record.",
"false": "Credits match the verified record."
}
},
"date_matches": {
"type": "noul",
"instructions": "Do all production dates match the supplied schedule?",
"criteria": {
"true": "A date conflicts with or is absent from the schedule.",
"false": "Dates match the supplied schedule."
}
}
}
DECISION RULES (in code, not in the model)
- choice/score: if confidence < 0.6 show a "needs review" badge instead of acting.
- noul: >= 0.75 = yes, <= 0.25 = no, otherwise "review".
- score: normalise with score / (levels - 1) before combining with weights.
- Missing or malformed answers go to review. Show safe HTTP status and message in the UI. Retry only 429/5xx,
at most twice with increasing delay; never retry 400/401/402/403/404 and never invent results.
- If the product needs prose (a summary, a message), use Lovable AI for that text only; Jev makes the decisions.
UI
a checklist of conditions, each with a 0-1 probability meter and a pass / review / fail colour from code-owned thresholds. Include 2 sample inputs as one-click chips so the demo works instantly.
Tailwind + shadcn, editorial look, footer: "Built during the Creative AI & Quantum Hackathon organised by StreetKode Fam during Indian Krump Festival 14".
NO database, NO auth, NO extra pages, NO tests.
BEFORE YOU FINISH
- Run the app and test both sample inputs through the real server function.
- Confirm the browser receives no API key and no fabricated fallback result.
- Confirm Choice/Score confidence and Noul probability drive the stated review rules.
- Confirm loading, success, review, empty-input, and service-error states are readable on mobile.
Reference only if needed: https://docs.typesafe.ai/api and https://docs.typesafe.ai/primitives
Market sizing.
TAM
Publishing and arts administration software: ~$1.3B/yr
SAM
Theatre program-production tools: ~$85M/yr
SOM
Company pilots: ~$400K/yr
Indicative figures for hackathon pitches — refine with your own research before raising.
Adjacent entries.
Stage management
Scene Change Sentinel
Paste scene text and changeover notes; Jev independently checks for unsafe, impractical, and under-specified transitions, and code flags a changeover if any check fails.
PlaywritingSubtext Signal Board
Paste a scene and character objectives; Jev independently checks whether each objective is legible in the dialogue, contradicted by action, or shared by multiple characters, and code flags scenes meeting chosen conditions.
Props managementProp Continuity Ledger
Paste a script excerpt and prop tracking notes; Jev independently checks for untracked entrances, unexplained prop transfers, and inconsistent prop states, and code creates a continuity alert when any check is true.
Lighting designCue Sheet Compass
Paste a script beat sheet and lighting cue list; Jev independently checks whether cues match beat changes, have clear triggers, and conflict with blackout or scene timing, and code routes flagged cues for review.