| name | glmv-doc-based-writing |
| description | Write a textual content based on given document(s) and requirements, using ZhiPu GLM-V multimodal model. Read and comprehend one or multiple documents (PDF/DOCX), write a content in Markdown format according to the specified requirements. Use when the user wants to draft a paper/article/essay/report/review/post/brief/proposal/plan, etc. |
| metadata | {"openclaw":{"requires":{"env":"[Truncated]","bins":"[Truncated]"},"primaryEnv":"ZHIPU_API_KEY","emoji":"✍️","homepage":"https://github.com/zai-org/GLM-V/tree/main/skills/glmv-doc-based-writing"}} |
GLM-V Document-Based Writing Skill
Comprehend the given document(s) and write a textual content (paper/article/essay/report/review/post/brief/proposal/plan) according to your requirements using the ZhiPu GLM-V multimodal model.
When to Use
- Write a textual content according to specified requirements, AFTER reading provided document(s)
- User mentions "基于文档的写作", "文章撰写", "文档解读", "新闻稿撰写", "简报撰写", "影评/书评撰写", "内容总结", "内容创作", "评论写作", "文档续写", "文档翻译", "方案策划", "发言稿撰写", "document-based writing", "article writing", "document reading", "press release writing", "brief writing", "film/book review writing", "content summarization", "content creation", "commentary writing", "document continuation", "document translation", "proposal planning ", "speech writing"
Supported Input Types
| Type | Formats | Max Count | Source |
|---|
| Document (URL) | pdf, docx | 50 | URL |
| Document (Local) | pdf only | pages ≤ 50 total | Local path |
Local PDF / 本地 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.
本地 PDF 会自动逐页转为图片（base64）传给模型，需要安装 PyMuPDF（pip install PyMuPDF）。URL 文件支持 pdf/docx/txt 等全格式。
📋 Output Display Rules (MANDATORY)
After running the script, you must display the complete content (Markdown format) exactly as returned. Do not summarize, truncate, translate, comment, or only say "Writing Completed!".
Resource Links
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.
脚本通过 ZHIPU_API_KEY 环境变量获取密钥，与其他智谱技能共用同一个 key。
Get Key / 获取 Key： Visit Zhipu Open Platform API Keys / 智谱开放平台 API Keys to create or copy your key.
Setup options / 配置方式（任选一种）：
-
OpenClaw config (recommended) / OpenClaw 配置（推荐）： Set in openclaw.json under skills.entries.glmv-doc-based-writing.env:
"glmv-doc-based-writing": { "enabled": true, "env": { "ZHIPU_API_KEY": "你的密钥" } }
-
Shell environment variable / Shell 环境变量： 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.
💡 如果你已为其他智谱 skill（如 zhipu-tools、glmv-caption）配置过 key，它们共享同一个 ZHIPU_API_KEY，无需重复配置。
How to Use
Basic Screening
python scripts/doc_based_writing.py \
--files "https://example.com/doucment1.pdf" "https://example.com/doucment2.docx" \
--requirements "基于这篇论文撰写公众号文章，要求偏技术风格"
Save as Markdown
python scripts/doc_based_writing.py \
--files "https://example.com/doucment1.pdf" "https://example.com/doucment2.docx" \
--requirements "总结文档主要内容和核心观点" \
--output result.md
Save as JSON
python scripts/doc_based_writing.py \
--files "https://example.com/doucment1.pdf" "https://example.com/doucment2.docx" \
--criteria "撰写新闻稿" \
--output result.json --pretty
Custom System Prompt
python scripts/doc_based_writing.py \
--files "https://example.com/doucment1.pdf" \
--criteria "为这本书撰写书评" \
--system-prompt "你是一位拥有20年跨领域写作经验的资深写作专家，擅长撰写书评"
Output Example
The model outputs a Markdown content like this:
XXX
CLI Reference
python scripts/doc_based_writing.py --files FILE [FILE...] --requirements REQUIREMENTS [OPTIONS]
| Parameter | Required | Description |
|---|
--files, -f | ✅ | Document file URLs (pdf/docx, URL only, max 50) |
--requirements, -c | ✅ | Writing requirements 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: 0.6) |
--max-tokens | No | Max output tokens (default: 10000) |
--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: → Documents too large or too many → reduce file count
