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jev-playground

ozanedge/jev-playground

Scaffold app using Jev for typed decisions and copy-clarity audits.

Other0.64Runner-up: Infra / SDKs / IntegrationsQuestionnaireScorecard
Automated README summary

Automatically summarized from the README on 29 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A Next.js/TypeScript playground for TypeSafe's Jev System One model. It ships a placeholder decide endpoint and an `npm run audit` CLI that reads your current Chrome tab and ranks hard-to-understand copy. The app itself is still to be built.

How it uses Jev

Jev answers typed questions about page text: each on-screen control, heading, column, field and message gets 2–3 narrow yes/no questions, batched 30 elements per request and sent in parallel. Code inverts, combines and weights the probabilities, then ranks issues. The example triage decision is a placeholder endpoint.

Primitives:choicescorenoul

Technique worth stealing

Turn a page into text, ask many narrow yes/no questions per element, then combine and weight probabilities in code.

Try it

npm install; cp .env.example .env.local; add TYPESAFE_API_KEY; npm run dev

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.90
  • Shows a System One patternnot found in the excerpt0.23
  • Describes handling uncertaintynot found in the excerpt0.04
  • Reports measured numbersnot found in the excerpt0.04
  • Is a runnable toolFound in material0.94
  • Top-10 learning shortlist signalnot found in the excerpt0.16
  • Is a replica of the modelnot found in the excerpt0.03
  • Solves a common problem (0–2)score on a 0–2 scale0.10 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.90Shows a System One pattern0.23Describes handling uncertainty0.04Reports measured numbers0.04Is a runnable tool0.94Top-10 learning shortlist signal0.16Is a replica of the model0.0300.51Solves a common problem (0–2)0.10 / 2012

no-judgment band (0.40–0.60)

Design patterns
Scorecard0.95Questionnaire0.85Funnel0.62Question bank0.39Traffic light0.2600.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 29 Sept 2026.