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building-with-typesafe-jev

mustafadeluca/building-with-typesafe-jev · Homepage

Unofficial skill teaching coding agents to build with TypeSafe Jev.

Agent Decisions0.93Runner-up: Calibration & ResearchQuestionnaire
Automated README summary

Automatically summarized from the README on 14 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

An unofficial community skill that teaches coding agents to design for TypeSafe Jev, a System One model. It provides typed decision patterns and links to 150+ community projects, sorted by shape, with code sketches. Installs in Claude Code, Codex, Antigravity CLI, Muse, and Muse Code.

How it uses Jev

Jev takes content and typed questions (Choice, Score, Noul) and returns a value with calibrated probability in 100-200 ms. The skill helps agents design these questions and use the results in code, such as routing tickets or grading pull requests.

Primitives:choicescorenoul

Technique worth stealing

Designing typed questions with calibrated confidence for System One models.

Try it

Install via plugin marketplace for your agent, e.g., claude plugin marketplace add aaddrick/building-with-typesafe-jev.

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 material0.83
  • Shows a System One patternunclear0.57
  • Describes handling uncertaintynot found in the excerpt0.06
  • Reports measured numbersnot found in the excerpt0.04
  • Is a runnable toolnot found in the excerpt0.22
  • Top-10 learning shortlist signalunclear0.40
  • Is a replica of the modelnot found in the excerpt0.05
  • Solves a common problem (0–2)score on a 0–2 scale1.00 / 2
  • About JevFound in material0.96
Signals
Jev is core to the project0.83Shows a System One pattern0.57Describes handling uncertainty0.06Reports measured numbers0.04Is a runnable tool0.22Top-10 learning shortlist signal0.40Is a replica of the model0.0500.51Solves a common problem (0–2)1.00 / 2012

no-judgment band (0.40–0.60)

Design patterns
Questionnaire0.80Menu0.66Funnel0.66Check-up0.45Ghostwriter0.40Inspection0.35Traffic light0.3300.51

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 14 Oct 2026.