Poem Sequence Map
Paste poem titles and texts, then Jev ranks possible sequences by tonal progression, thematic cohesion, and variety with your chosen weights.
Score Ranker· graded ranking
Section · Jev
full primer →The kernel.
Jev rates every option for Poetry collections on a few named qualities; writers move sliders to decide what matters and the ranking updates instantly.
Why this primitiveA weighted ranking helps poets compare arrangements while leaving the final artistic order in their hands.
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 "Poem Sequence Map" 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 poem titles and texts, then Jev ranks possible sequences by tonal progression, thematic cohesion, and variety with your chosen weights.
Discipline: Writing, Poetry & Narrative (Poetry collections).
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: A weighted ranking helps poets compare arrangements while leaving the final artistic order in their hands.
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": <Poem texts, titles, and collection theme>, "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)
{
"tonal_progression": {
"type": "score",
"instructions": "How well does this sequence create a satisfying tonal journey?",
"criteria": [
"Flat or jarring",
"Some movement, unevenly paced",
"Clear and mostly effective arc",
"Nuanced, purposeful tonal journey"
]
},
"thematic_cohesion": {
"type": "score",
"instructions": "How strongly do the poems belong in the same collection?",
"criteria": [
"Little shared territory",
"Loose or inconsistent connection",
"Clear shared concerns",
"Rich, resonant collection-wide cohesion"
]
},
"variety": {
"type": "score",
"instructions": "How well does the sequence balance different forms, subjects, and energies?",
"criteria": [
"Repetitive throughout",
"Some contrast, mostly similar",
"Good variety with a few clusters",
"Distinctive variety with purposeful echoes"
]
}
}
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
$500M poetry publishing and tools market
SAM
$80M collection-planning segment
SOM
$500K poetry-workshop and indie segment
Indicative figures for hackathon pitches — refine with your own research before raising.
Adjacent entries.
Novel development
Opening Page Sorter
Paste several opening pages and Jev scores and ranks them for hook, clarity, and voice using weights you set.
ScreenwritingScene Cut Compass
Paste a screenplay scene and its surrounding scene list, then Jev scores candidate cut points for momentum, continuity, and emotional landing.
Character dialogueDialogue Voice Ledger
Paste dialogue samples for several characters and Jev scores each line for voice distinction, character fit, and subtext using your weights.
Narrative designQuestline Priority Grid
Paste quest summaries and design goals, then Jev ranks quests by player agency, story relevance, and implementation clarity using adjustable weights.