glmv-resume-screen

Name: glmv-resume-screen
Availability: InStock
Author: ViewWay

Screen up to 50 resumes against criteria using GLM-V models.

Updated Apr 2, 2026

Search Tags:#automation #pdf #ai #multimodal #docx #resume screening #glm-v

Ready to run

npx skills add https://github.com/ViewWay/openclaw-skills --skill glmv-resume-screen-viewway

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: glmv-resume-screen
Source: https://github.com/ViewWay/openclaw-skills/tree/main/glmv-resume-screen
Command: npx skills add https://github.com/ViewWay/openclaw-skills --skill glmv-resume-screen-viewway

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the tedious manual process of screening a large number of resumes by leveraging the GLM-V multimodal model to evaluate candidates against user-defined criteria and present results in a structured Markdown table.

Core Features & Use Cases

Batch-read resumes from PDFs, DOCX, and TXT formats (via URLs or local files) and evaluate them against your criteria.
Output a Markdown table with per-candidate pass/fail, match level, and reasoning to support hiring decisions.
Ideal for recruiter workflows: fast screening of applicants, comparison across candidates, and batch evaluation for job postings.

Quick Start

Run the resume-screen script with a list of resume file URLs or local PDFs and a screening criteria string to generate a Markdown result 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 automate resume screening against specific job criteria?▼

Automate resume screening by running the script with local PDFs or remote URLs alongside a screening criteria string to evaluate candidates using the GLM-V multimodal model. It processes up to 50 resumes and outputs a Markdown table detailing pass/fail analysis per candidate.

Can I evaluate DOCX and TXT files along with PDFs for candidate screening?▼

Yes, you can evaluate DOCX and TXT files in addition to PDFs for candidate screening. The skill supports batch reading from multiple formats via local files or remote URLs to analyze applicant qualifications against your defined criteria.

Do I need a ZHIPU_API_KEY to run multimodal resume analysis?▼

Yes, you need a ZHIPU_API_KEY to run multimodal resume analysis. This key is required to authenticate requests to the GLM-V model, which evaluates candidate qualifications and generates the pass/fail reasoning table.

What is the maximum number of resumes I can batch screen in a single run?▼

The maximum number of resumes you can batch screen in a single run is 50. The skill enforces input validation and limits to ensure stable processing when generating the Markdown results table for your candidate evaluation.

Can I mix local PDF files and remote URLs when batch screening resumes?▼

No, you cannot mix local PDF files and remote URLs when batch screening resumes. The skill enforces input validation that prevents combining local and remote sources to avoid processing errors during evaluation.

How does AI resume screening present pass/fail results for candidates?▼

AI resume screening presents pass/fail results by generating a structured Markdown table. This table details match levels and reasoning for each candidate evaluated against your criteria, supporting direct comparison across applicants.