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glmv-resume-screen

Screen up to 50 PDF, DOCX, or TXT resumes against hiring criteria and output a Markdown table.

458|40|Updated Mar 30, 2026
Search Tags:#pdf#resume#docx#screening#hr#candidate-evaluation#glm-v
One-click install
npx skills add https://github.com/zai-org/GLM-skills --skill glmv-resume-screen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: glmv-resume-screen
Source: https://github.com/zai-org/GLM-skills/tree/main/skills/glmv-resume-screen
Command: npx skills add https://github.com/zai-org/GLM-skills --skill glmv-resume-screen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, PyMuPDF, and includes scripts (resource) components.

What problem does it solve?

Recruiters and hiring managers spend significant time manually reading and comparing resumes; this Skill automates bulk resume screening and produces consistent, comparable pass/fail evaluations against explicit hiring criteria.

Core Features & Use Cases

  • Batch resume ingestion: Accepts up to 50 remote files (pdf/docx/txt) or local PDFs (converted page-by-page to images) for group screening.
  • Criteria-based evaluation: Compares each resume against user-defined screening criteria and outputs a strict Markdown table with pass/fail, match level, and concise reasoning.
  • CLI tooling and exports: Command-line interface supports custom system prompts, model selection, temperature and token limits, and saving results as Markdown or JSON for HR workflows.
  • Use Case: Screen a pool of applicants for required experience, technical skills, or education level and receive a ready-to-review Markdown table for hiring decisions.

Quick Start

Ask the assistant to screen the provided resume URLs against "3+ years Python backend experience and project leadership" and return the full Markdown table.

Frequently Asked Questions about glmv-resume-screen

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I batch screen resumes against specific hiring criteria?▼

To batch screen resumes, provide up to 50 remote PDF, DOCX, or TXT files along with your defined hiring criteria. The Skill evaluates candidate fit and outputs a strict Markdown table with pass/fail, match level, and reasoning.

Can I use GLM-V multimodal AI for local PDF resume screening?▼

Yes, local PDF resume screening is supported by converting PDF pages to images for GLM-V multimodal AI evaluation. The system requires a valid ZHIPU_API_KEY to process the visual resume data against your hiring criteria.

Do I need a ZHIPU_API_KEY to evaluate candidate fit with this tool?▼

Yes, a valid ZHIPU_API_KEY is required for API access to evaluate candidate fit. The key enables the GLM-V multimodal model to process resumes and generate comparison tables based on your custom system prompts.

What is the best way to export resume screening results for HR workflows?▼

The best way to export resume screening results is by using the command-line interface to save outputs as Markdown or JSON files. This allows HR workflows to directly integrate the pass/fail evaluations, match levels, and reasoning into downstream systems.

Does the resume screening CLI support custom temperature and token limits?▼

Yes, the command-line interface supports custom system prompts, model selection, temperature, and token limits. These configurations allow you to control the GLM-V model's evaluation behavior when screening candidate resumes.

What are the limitations when processing bulk PDF resumes for candidate comparison?▼

A key limitation is that batch processing is capped at 50 remote files per run, and local processing is restricted to PDFs converted page-by-page to images. Exceeding this volume requires splitting the applicant pool into multiple batches.

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