How is the tenure math different from asking a chat model?

It merges overlapping intervals into true chronological tenure instead of summing each job line, so concurrent internships and freelance gigs are not double-counted the way a free-text summary can.

Can I run it without a TypeSafe key?

Yes. Without a key it runs in high-speed local mode on deterministic rules. Setting TYPESAFE_API_KEY enables the Jev decision gateway and the key-connectivity test endpoint.

What does a rejected candidate's audit trail contain?

Every rejection pairs the requirement with a verbatim quote or verifiable absence, plus one-click audit notices and CSV or JSON roster exports with timestamps, model versions and citations.

How do resume batches get in and verdicts get out?

Drop PDF, DOCX, TXT or Markdown batches, or paste text to the evaluate endpoint. Sample resumes and role templates are included, and the REST endpoints wire the same flow into an ATS.

What does the decision pipeline do?

Layer 1 computes true non-overlapping calendar tenure by resolving overlaps, layer 2 applies deterministic hard gates for visa status, minimum tenure, licenses, and clearances, and layer 3 calls Jev System One for a calibrated micro-decision.

How do I run it and integrate it?

pip install -r requirements.txt, optionally set TYPESAFE_API_KEY, then python gui/server.py opens the dashboard at localhost:8990. A REST API exposes /api/upload_resumes, /api/evaluate_text, /api/update_jd, and CSV and JSON export endpoints.

What license is it under?

MIT, built by AIPersona Academy (APA). It runs in a local rule-based mode with no TypeSafe key and uses the Jev gateway when one is supplied.

CommunityJev Tools & CLIs

Jev Resume Disqualifier

Recruiter dashboard that applies calendar date math plus visa, tenure, license and clearance gates, then a Jev decision step, sorting resumes into disqualified, advance or manual review.

See highlights

Open github.com

Stars: 3
Language: Python
License: MIT
Published by: Community
Author: AiPersonacademy
Last verified: Oct 2026

AiPersonacademy/jev-resume-disqualifier

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Jev Resume Disqualifier: Sub-25ms automated resume knockout engine powered by TypeSafe Jev System One decision intelligence. Eliminates 80% of unqualified applicants with deterministic date math & EEOC-safe rejection notices.

Forks: 0
Last pushed: Updated Sep 2026

Repo stats from the GitHub API, cached Oct 2026.

About this project

Every open corporate role today receives 300 to 1,500+ applications. Over 80% are immediately unqualified: Candidates with 1.5 years of experience applying for Senior roles requiring 5+ years. Candidates requiring H1B visa sponsorship applying to roles with strict US-only work authorization. Candidates applying to medical, engineering, or legal roles without mandatory state licenses. Recruiting teams and hiring managers waste 15 to 25 hours every week manually scanning dates and writing rejection letters.

Quoted from the project's README. Read the full README.

Tagscommunity jevbest catalog-import awesomejev

Works forJev for Classification Jev for Routing

Used inJev for Software & DevTools

Languages: Python

Highlights

Layered pipeline: non-overlapping date math, hard knockout gates, then a Jev decision gateway.
Dealbreakers cover tenure, work authorization, licenses, clearance and custom rules.
Verdicts show exact factual deficits and ship with citable rejection notices.
Dashboard on local port plus REST endpoints for profiles, uploads, evaluation and exports.

Watch out

Without a TypeSafe key the engine runs in local deterministic rule mode; the latency and cost comparison table is the author's claim and borderline cases are left to manual review. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

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