Lore Glossary Linker
Paste worldbuilding notes and a chapter, and Jev links each glossary entry to the best matching extracted passage, or none.
Select, Don't Generate· pick the real value
Section · Jev
full primer →The kernel.
Instead of writing new text, the app finds real candidates in the material and Jev picks the right one, so writers get exact values for Worldbuilding.
Why this primitiveExact passage links let authors verify how invented terms appear in the manuscript without generated lore explanations.
Kernel
code extracts candidate spans/values from the source, then a Jev `choice` (with a 'none' option) selects the intended one so the app copies real text instead of generating it
Drives the UI as
the source text with candidate spans highlighted and the selected one locked in
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 "Lore Glossary Linker" 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 worldbuilding notes and a chapter, and Jev links each glossary entry to the best matching extracted passage, or none.
Discipline: Writing, Poetry & Narrative (Worldbuilding).
Jev pattern: Select, Don't Generate (pick the real value) — code extracts candidate spans/values from the source, then a Jev `choice` (with a 'none' option) selects the intended one so the app copies real text instead of generating it.
Why typed decisions: Exact passage links let authors verify how invented terms appear in the manuscript without generated lore explanations.
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": <Glossary entries, chapter text, and extracted candidate spans>, "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)
{
"glossary_reference": {
"type": "choice",
"instructions": "Which candidate uses or explains this glossary entry?",
"criteria": {
"candidate_1": "Directly uses or explains the entry",
"candidate_2": "Directly uses or explains the entry",
"candidate_3": "Directly uses or explains the entry",
"none": "No candidate relates to the entry"
}
},
"meaning_consistency": {
"type": "noul",
"instructions": "Does the selected passage use the entry consistently with its glossary definition?",
"criteria": {
"true": "The passage appears to contradict the definition",
"false": "The passage is consistent with the definition"
}
}
}
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
the source text with candidate spans highlighted and the selected one locked in. 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
$1.8B narrative and game development tools
SAM
$230M worldbuilding and lore management software
SOM
$2M fiction and tabletop creator segment
Indicative figures for hackathon pitches — refine with your own research before raising.
Adjacent entries.
Worldbuilding
Lore Consistency Switchboard
Paste a fictional-world passage and Jev routes it to a lore domain, then scores consistency with the supplied canon and checks for an explicit canon conflict.
WorldbuildingSetting Detail Curator
Paste setting details and a scene summary, then Jev ranks details for atmosphere, story relevance, and internal consistency with adjustable weights.
Novel revisionMotif Thread Finder
Paste a chapter and Jev selects which extracted phrase best echoes an earlier motif, or none, so the app can link the original text.
ScreenwritingScene Turn Marker
Paste a screenplay scene and Jev selects an extracted line or action beat that signals the scene’s turning point, or none.