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jev-resume-analyzer

awun8191/jev-resume-analyzer · Homepage

Resume analysis with typed Jev judgments: content, structure, job alignment.

Automated README summary

Automatically summarized from the README on 30 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A browser-based resume and CV analyzer for job seekers: upload a PDF or DOCX to get a 0–100 content score, layout checks, and optional job alignment, with traceable findings.

How it uses Jev

Jev makes typed judgments over the whole document: twenty content questions across seven dimensions, three job-alignment questions when a posting is pasted, and eleven structure checks over page images. Each returns an answer with a probability distribution; scores are weighted in code and shown with the question, criteria, and probabilities.

Primitives:choicescore

Technique worth stealing

Compose typed rubric questions in code and weight their calibrated answers into scores, keeping every finding traceable to its question and distribution.

Try it

Run backend with uv run uvicorn app.main:app --port 8017 and frontend with npm run dev; open http://127.0.0.1:5273.

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 material0.96
  • Shows a System One patternFound in material0.92
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.07
  • Is a runnable toolFound in material0.80
  • Top-10 learning shortlist signalunclear0.59
  • Is a replica of the modelnot found in the excerpt0.03
  • Solves a common problem (0–2)score on a 0–2 scale0.99 / 2
  • About JevFound in material0.99
Signals
Jev is core to the project0.96Shows a System One pattern0.92Describes handling uncertainty0.03Reports measured numbers0.07Is a runnable tool0.80Top-10 learning shortlist signal0.59Is a replica of the model0.0300.51Solves a common problem (0–2)0.99 / 2012

no-judgment band (0.40–0.60)

Design patterns
Scorecard0.96Questionnaire0.84Fail open, fail closed0.78Question bank0.54Funnel0.44Inspection0.2700.51

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 30 Oct 2026.