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searchjev

mita-pixels/searchjev

Firefox extension re-ranks Google results with Jev to demote SEO mass-produced articles.

Scoring & Ranking1.00Runner-up: Classification & RoutingQuestionnaireScorecard
Automated README summary

Automatically summarized from the README on 17 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

SearchJev is a Firefox extension for desktop and Android that re-ranks Google search results, pushing down mass-produced SEO/affiliate articles and lifting official and first-hand sources. It shows per-result sub-scores and needs a TypeSafe API key.

How it uses Jev

For each result, background.js sends the query plus the result's title, snippet, domain and URL path to Jev as six bundled questions. Jev returns probabilities and graded judgments, which defaults.js combines into a weighted total score; content.js displays the scores and reorders results.

Primitives:choicescorenoul

Technique worth stealing

Bundle six typed judgment questions per result, then combine the calibrated answers into a weighted total score for re-ranking.

Try it

Load extension/manifest.json via about:debugging in Firefox; no build step.

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 material0.91
  • Shows a System One patternnot found in the excerpt0.33
  • Describes handling uncertaintynot found in the excerpt0.37
  • Reports measured numbersnot found in the excerpt0.05
  • Is a runnable toolFound in material0.98
  • Top-10 learning shortlist signalnot found in the excerpt0.35
  • Is a replica of the modelnot found in the excerpt0.06
  • Solves a common problem (0–2)score on a 0–2 scale1.14 / 2
  • About JevFound in material0.98
Signals
Jev is core to the project0.91Shows a System One pattern0.33Describes handling uncertainty0.37Reports measured numbers0.05Is a runnable tool0.98Top-10 learning shortlist signal0.35Is a replica of the model0.0600.51Solves a common problem (0–2)1.14 / 2012

no-judgment band (0.40–0.60)

Design patterns
Scorecard0.97Questionnaire0.93Check-up0.66Viewfinder0.54Question bank0.44Funnel0.31Grey zone0.2800.51

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 17 Oct 2026.