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jev-judge-mcp

swami8791/jev-judge-mcp

Owner-private ChatGPT integration for typed Jev judgments.

Automated README summary

Automatically summarized from the README on 31 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

An MCP server that lets a ChatGPT assistant submit text with explicit questions to TypeSafe Jev and receive typed scores, categories, or yes/no probabilities, with rubric, uncertainty, and review flags kept visible for the owner.

How it uses Jev

The jev_evaluate tool sends one fixed provider request with state and questions (score, choice, noul) after validation and owner checks. Jev returns calibrated probabilities and scores, which the adapter normalizes into typed results with separate confidence, review, and verification fields; no retries or downstream actions.

Primitives:scorechoicenoul

Technique worth stealing

Fail-closed boundary: validate identity, owner, config, and input before a single fixed HTTPS provider call, then keep scores, confidence, and review flags as separate fields.

Try it

git clone https://github.com/swami8791/jev-judge-mcp.git && cd jev-judge-mcp && npm test (Node 22.13+).

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-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

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 material0.80
  • Shows a System One patternnot found in the excerpt0.08
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.02
  • Is a runnable toolFound in material0.83
  • Top-10 learning shortlist signalnot found in the excerpt0.13
  • Is a replica of the modelnot found in the excerpt0.10
  • Solves a common problem (0–2)score on a 0–2 scale1.08 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.80Shows a System One pattern0.08Describes handling uncertainty0.03Reports measured numbers0.02Is a runnable tool0.83Top-10 learning shortlist signal0.13Is a replica of the model0.1000.51Solves a common problem (0–2)1.08 / 2012

no-judgment band (0.40–0.60)

Design patterns
Questionnaire0.91Funnel0.75Inspection0.70Fail open, fail closed0.5800.51

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 31 Oct 2026.