Set Change Planner
Paste scene transitions, set pieces, and crew availability, and Jev scores each transition plan for safety, speed, and crew practicality for weighted ranking.
Score Ranker· graded ranking
Section · Jev
full primer →The kernel.
Jev rates every option for Stage management on a few named qualities; directors move sliders to decide what matters and the ranking updates instantly.
Why this primitiveTyped scores let teams compare concrete plans against operational priorities without relying on free-form recommendations.
Kernel
comparable Jev `score` questions per candidate on 3-4 named dimensions, normalised with score/(levels-1) and combined with user-controlled weights in code
Drives the UI as
a ranked list with weight sliders that re-rank instantly without calling Jev again
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 "Set Change Planner" 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 scene transitions, set pieces, and crew availability, and Jev scores each transition plan for safety, speed, and crew practicality for weighted ranking.
Discipline: Theater & Live Performance (Stage management).
Jev pattern: Score Ranker (graded ranking) — comparable Jev `score` questions per candidate on 3-4 named dimensions, normalised with score/(levels-1) and combined with user-controlled weights in code.
Why typed decisions: Typed scores let teams compare concrete plans against operational priorities without relying on free-form recommendations.
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": <Scene sequence, set pieces, crew and stage constraints>, "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)
{
"changeover_safety": {
"type": "score",
"instructions": "For each plan, score the safety of the described movement and handling.",
"criteria": [
"1 — Serious unresolved hazards",
"2 — Significant risks remain",
"3 — Generally safe with precautions",
"4 — Clear, well-controlled movement"
]
},
"changeover_speed": {
"type": "score",
"instructions": "For each plan, score how quickly the change can be completed in the stated conditions.",
"criteria": [
"1 — Unlikely to meet timing",
"2 — Tight or inconsistent timing",
"3 — Likely to meet timing",
"4 — Fast with comfortable margin"
]
},
"crew_practicality": {
"type": "score",
"instructions": "For each plan, score whether the assigned crew can execute it reliably.",
"criteria": [
"1 — Roles or sequence are unworkable",
"2 — Significant coordination burden",
"3 — Roles and sequence are workable",
"4 — Clear, robust, low-friction execution"
]
}
}
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 ranked list with weight sliders that re-rank instantly without calling Jev again. 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
Global production management software: ~$3B/year
SAM
Theater stage-management tools: ~$300M/year
SOM
Early theater customers: ~$1M/year
Indicative figures for hackathon pitches — refine with your own research before raising.
Adjacent entries.
Stage management
Scene Shift Mapper
A stage manager pastes scene summaries and changeover notes, and Jev routes each transition to a preset, crew shift, or scenic automation plan.
Stage managementScene 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.
CastingAudition Callback Sorter
Paste audition sides and performer profiles, and Jev scores each performer for role fit, emotional range, and ensemble balance before your adjustable weights rank callbacks.
DramaturgyScene Cut Compass
Paste a script and proposed cut points, and Jev scores each cut for plot clarity, character continuity, and playable rhythm for a weighted ranking.