Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add dqtx760/glm4v-vision-mcp --skill glm-4v-visiongit clone --depth 1 https://github.com/dqtx760/glm4v-vision-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/dqtx760/glm4v-vision-mcp/glm-4v-vision)<a href="https://agentmods.dev/skills/dqtx760/glm4v-vision-mcp/glm-4v-vision"><img src="https://agentmods.dev/badge/skills/dqtx760/glm4v-vision-mcp/glm-4v-vision/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/dqtx760/glm4v-vision-mcp/glm-4v-vision"><img src="https://agentmods.dev/badge/skills/dqtx760/glm4v-vision-mcp/glm-4v-vision.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.00521 |
| Opus 5 | $0.00023 | $0.00260 |
| Sonnet 5 | $0.00009 | $0.00104 |
| Haiku 4.5 | $0.00005 | $0.00052 |
Grade A, and why
glm-4v-vision scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
GLM-4V Flash 图片识别 Skill
使用智谱 AI 的 GLM-4V Flash 模型进行图片内容识别。
前置条件
确保已设置环境变量 ZHIPU_API_KEY（智谱 AI API Key）。
可用工具
1. analyze_image - 图片分析
分析图片内容，支持自定义提示词。
参数：
image_path(必填): 图片文件路径prompt(可选): 分析提示词，默认 "请详细描述这张图片的内容"
示例：
分析图片内容：D:\images\photo.jpg，提示词：描述图片中的场景和人物
2. extract_text - 文字提取 (OCR)
从图片中提取文字内容。
参数：
image_path(必填): 图片文件路径language(可选): 文字语言，可选chinese、english、auto，默认auto
示例：
提取图片文字：D:\images\doc.png，语言：chinese
3. describe_image - 图片描述
生成图片的详细描述，支持多种风格。
参数：
image_path(必填): 图片文件路径style(可选): 描述风格，可选detailed、concise、poetic、technical，默认detailed
示例：
描述图片：D:\images\art.jpg，风格：detailed
使用流程
- 用户指定图片路径和分析需求
- 调用对应的 MCP 工具（analyze_image / extract_text / describe_image）
- 返回 GLM-4V Flash 的分析结果
支持的图片格式
- PNG
- JPG / JPEG
- WebP
- GIF
- BMP
注意事项
- 图片会自动压缩至最大边长 2048 像素，以优化传输速度
- 需要有效的智谱 AI API Key
- 支持中文和英文提示词
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 74 lines · 47 tokens per session scan A e356254f6946
glm-4v-vision is a skill published in the GitHub repository dqtx760/glm4v-vision-mcp (8 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 521 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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