Glmocr Table logo

Glmocr Table

Organization
zai-org
glmocr-table

Official skill for recognizing and extracting tables from images and PDFs into Markdown format using ZhiPu GLM-OCR API. Supports complex tables, merged cells, and multi-page documents. Use this skill when the user wants to extract tables, recognize spreadsheets, or convert table images to editable format.

Overview

Publisherzai-org
RepositoryGLM-skills
Skill nameglmocr-table
Stars
476
Forks
45
Bundled files
1
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zai-org on GitHub. Read the source before you install it.

Installation

Install the Glmocr Table AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-table
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zai-org/GLM-skills.git /tmp/GLM-skills
mkdir -p .claude/skills
cp -r /tmp/GLM-skills/skills/glmocr-table .claude/skills/glmocr-table
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Glmocr Table in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Glmocr Table on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Glmocr Table is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GLM-OCR Table Recognition Skill / GLM-OCR 表格识别技能

Extract tables from images and PDFs and convert them to Markdown format using the ZhiPu GLM-OCR layout parsing API.

When to Use / 使用场景

  • Extract tables from images or scanned documents / 从图片或扫描件中提取表格
  • Convert table images to Markdown or Excel format / 将表格图片转为 Markdown 或可编辑格式
  • Recognize complex tables with merged cells / 识别含合并单元格的复杂表格
  • Parse financial statements, invoices, reports with tables / 解析财务报表、发票、带表格的报告
  • User mentions "extract table", "recognize table", "表格识别", "提取表格", "表格OCR", "表格转文字"

Key Features / 核心特性

  • Complex table support: Handles merged cells, nested tables, multi-row headers
  • Markdown output: Tables are output in clean Markdown format, easy to edit and convert
  • Multi-page PDF: Supports batch extraction from multi-page PDF documents
  • Local file & URL: Supports both local files and remote URLs

Resource Links / 资源链接

Prerequisites / 前置条件

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

脚本通过 ZHIPU_API_KEY 环境变量获取密钥,可与其他智谱技能复用同一个 key。 This script reads the key from the ZHIPU_API_KEY environment variable. Reusing the same key across Zhipu skills is optional.

Get Key / 获取 Key: Visit 智谱开放平台 API Keys to create or copy your key.

Setup options / 配置方式(任选一种):

  1. Global config (recommended) / 全局配置(推荐): Set once in openclaw.json under env.vars, all Zhipu skills will share it:

    json
    {
      "env": {
        "vars": {
          "ZHIPU_API_KEY": "你的密钥"
        }
      }
    }
  2. Skill-level config / Skill 级别配置: Set for this skill only in openclaw.json:

    json
    {
      "skills": {
        "entries": {
          "glmocr-table": {
            "env": {
              "ZHIPU_API_KEY": "你的密钥"
            }
          }
        }
      }
    }
  3. Shell environment variable / Shell 环境变量: Add to ~/.zshrc:

    bash
    export ZHIPU_API_KEY="你的密钥"

💡 如果你已为其他智谱 skill(如 glmocr、glmv-caption、glm-image-generation)配置过 key,它们共享同一个 ZHIPU_API_KEY,无需重复配置。

Security & Transparency / 安全与透明度

  • Environment variables used / 使用的环境变量:
    • ZHIPU_API_KEY (required / 必需)
    • GLM_OCR_TIMEOUT (optional timeout seconds / 可选超时秒数)
  • Fixed endpoint / 固定官方端点: https://open.bigmodel.cn/api/paas/v4/layout_parsing
  • No custom API URL override / 不支持自定义 API URL 覆盖: this avoids accidental key exfiltration via redirected endpoints.
  • Raw upstream response is optional / 原始响应默认不返回: use --include-raw only when needed for debugging.

⛔ MANDATORY RESTRICTIONS / 强制限制 ⛔

  1. ONLY use GLM-OCR API — Execute the script python scripts/glm_ocr_cli.py
  2. NEVER parse tables yourself — Do NOT try to extract tables using built-in vision or any other method
  3. NEVER offer alternatives — Do NOT suggest "I can try to recognize it" or similar
  4. IF API fails — Display the error message and STOP immediately
  5. NO fallback methods — Do NOT attempt table extraction any other way

📋 Output Display Rules / 输出展示规则

After running the script, present the OCR result clearly and safely.

  • Show extracted table Markdown (text) in full
  • Summarization is allowed, but do not hide important extraction failures
  • If layout_details contains table-related entries, you may highlight them
  • If the result file is saved, tell the user the file path
  • Show raw upstream response only when explicitly requested or debugging (--include-raw)

How to Use / 使用方法

Extract from URL / 从 URL 提取

bash
python scripts/glm_ocr_cli.py --file-url "https://example.com/table.png"

Extract from Local File / 从本地文件提取

bash
python scripts/glm_ocr_cli.py --file /path/to/table.png

Save Result to File / 保存结果到文件

bash
python scripts/glm_ocr_cli.py --file table.png --output result.json --pretty

Include Raw Upstream Response (Debug Only) / 包含原始上游响应(仅调试)

bash
python scripts/glm_ocr_cli.py --file table.png --output result.json --include-raw

CLI Reference / CLI 参数

python {baseDir}/scripts/glm_ocr_cli.py (--file-url URL | --file PATH) [--output FILE] [--pretty] [--include-raw]
ParameterRequiredDescription
--file-urlOne ofURL to image/PDF
--fileOne ofLocal file path to image/PDF
--output, -oNoSave result JSON to file
--prettyNoPretty-print JSON output
--include-rawNoInclude raw upstream API response in result field (debug only)

Response Format / 响应格式

json
{
  "ok": true,
  "text": "| Column 1 | Column 2 |\n|----------|----------|\n| Data     | Data     |",
  "layout_details": [...],
  "result": null,
  "error": null,
  "source": "/path/to/file",
  "source_type": "file",
  "raw_result_included": false
}

Key fields:

  • ok — whether extraction succeeded
  • text — extracted text in Markdown (use this for display)
  • layout_details — layout analysis details
  • error — error details on failure

Error Handling / 错误处理

API key not configured:

ZHIPU_API_KEY not configured. Get your API key at: https://bigmodel.cn/usercenter/proj-mgmt/apikeys

→ Show exact error to user, guide them to configure

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

Rate limit (429): Quota exhausted → inform user to wait

File not found: Local file missing → check path

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Glmocr Table AI skill do?

Official skill for recognizing and extracting tables from images and PDFs into Markdown format using ZhiPu GLM-OCR API. Supports complex tables, merged cells, and multi-page documents. Use this skill when the user wants to extract tables, recognize spreadsheets, or convert table images to editable format.

Why use Glmocr Table on TypingMind?

Because you install it once and use it with any model. Glmocr Table is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Glmocr Table in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zai-org/GLM-skills/tree/main/skills/glmocr-table. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Glmocr Table?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Glmocr Table?

As many as you like. As long as a model supports skills, you can use Glmocr Table with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Glmocr Table AI skill free?

Yes. It is published on GitHub by zai-org under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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