glmv-resume-screen

GLM-V Resume Screening Skill

Batch-read resumes and screen candidates against your criteria using the ZhiPu GLM-V multimodal model.

When to Use

Filter/screen multiple resumes against specific criteria
User mentions "filter resumes", "evaluate candidates", "resume screening", "resume screening", "filter candidates"
Compare candidates for a job position
Batch-evaluate job applications

Supported Input Types

Type	Formats	Max Count	Source
Resume (URL)	pdf, docx, txt	50	URL
Resume (Local)	pdf only	pages ≤ 50 total	Local path

Local PDF / Local PDF: Local PDF files are converted page-by-page into images (base64) before sending to the model. PyMuPDF is required (pip install PyMuPDF). URL files support full formats including pdf/docx/txt. Local PDFs are automatically converted page by page into images (base64) and passed to the model; requires installing PyMuPDF（pip install PyMuPDF). URL files support full formats including pdf/docx/txt.

📋 Output Display Rules (MANDATORY)

After running the script, you must display the complete screening result (Markdown table) exactly as returned. Do not summarize, truncate, or only say "screening completed". Users need each candidate's detailed analysis to decide.

Show the full Markdown table (index, name, pass/fail, match level, reasoning)
If output was saved (-o), provide the file path and show file content
If screening output is empty, explain why

Resource Links

Resource	Link
Get API Key	https://bigmodel.cn/usercenter/proj-mgmt/apikeys
API Docs	Chat Completions / Chat Completions

Prerequisites

API Key Setup / API Key 配置 (Required / 必需)

This script reads the key from the ZHIPU_API_KEY environment variable and shares it with other Zhipu skills. The script retrieves the key via the ZHIPU_API_KEY environment variable to retrieve the key, sharing the same key with other Zhipu skills.

Get Key / 获取 Key: Visit Zhipu Open Platform API Keys / Zhipu Open Platform API Keys to create or copy your key.

Setup options / 配置方式 (choose one):

OpenClaw config (recommended) / OpenClaw config (recommended): Set in openclaw.json under skills.entries.glmv-resume-screen.env:
```
"glmv-resume-screen": { "enabled": true, "env": { "ZHIPU_API_KEY": "你的密钥" } }
```
Shell environment variable / Shell environment variable: Add to ~/.zshrc:
```
export ZHIPU_API_KEY="你的密钥"
```

💡 If you already configured another Zhipu skill (for example zhipu-tools or glmv-caption), they share the same ZHIPU_API_KEY, so no extra setup is needed. 💡 If you have already configured a key for other Zhipu skills (such as zhipu-tools、glmv-caption), they share the same ZHIPU_API_KEY, no need to configure it again.

How to Use

Basic Screening

python scripts/resume_screen.py \
  --files "https://example.com/resume1.pdf" "https://example.com/resume2.docx" \
  --criteria "3年以上工作经验，有Python开发经验，有大型项目管理经验"

Save as Markdown

python scripts/resume_screen.py \
  --files "https://example.com/resume1.pdf" "https://example.com/resume2.docx" \
  --criteria "本科以上学历，5年后端开发经验" \
  --output result.md

Save as JSON

python scripts/resume_screen.py \
  --files "https://example.com/resume1.pdf" "https://example.com/resume2.docx" \
  --criteria "有机器学习经验" \
  --output result.json --pretty

Custom System Prompt

python scripts/resume_screen.py \
  --files "https://example.com/resume1.pdf" \
  --criteria "前端开发岗位，3年经验" \
  --system-prompt "你是一位资深技术面试官，特别关注候选人的项目深度和技术选型能力"

Output Example

The model outputs a Markdown table like this:

| 序号 | 候选人姓名 | 是否符合    | 符合程度 | 原因分析                                                    |
| ---- | ---------- | ----------- | -------- | ----------------------------------------------------------- |
| 1    | 张三       | ✅ 符合     | 高       | 5年后端经验，熟练使用Python和Django，主导过3个大型项目      |
| 2    | 李四       | ❌ 不符合   | 低       | 仅1年开发经验，主要使用Java，无Python经验                   |
| 3    | 王五       | ⚠️ 部分符合 | 中       | 3年Python经验但无项目管理经验，技术栈匹配但缺乏大型项目经历 |

CLI Reference

python scripts/resume_screen.py --files FILE [FILE...] --criteria CRITERIA [OPTIONS]

Parameter	Required	Description
`--files`, `-f`	✅	Resume file URLs (pdf/docx/txt, URL only, max 50)
`--criteria`, `-c`	✅	Screening criteria text
`--model`, `-m`	No	Model name (default: `glm-4.6v`)
`--system-prompt`, `-s`	No	Custom system prompt (default: professional HR assistant)
`--temperature`, `-t`	No	Sampling temperature 0-1 (default: 0.3)
`--max-tokens`	No	Max output tokens (default: 4096)
`--output`, `-o`	No	Save result to file (`.md` for markdown, `.json` for JSON)
`--pretty`	No	Pretty-print JSON output

Error Handling

API key not configured: → Guide user to configure ZHIPU_API_KEY

Authentication failed (401/403): → API key invalid/expired → reconfigure

Rate limit (429): → Quota exhausted → wait and retry

Local path provided: → Error: only URLs supported

Content filtered: → warning field present → content blocked by safety review

Timeout: → Resumes too large or too many → reduce file count