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Local GMNCODE Vision

作者 iO2077 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install local-gmncode-vision
功能描述
当内置 image 工具不可用、但本机配置了 GMNCODE_API_KEY 时,使用本地脚本直连 GMNCODE Responses API 完成图片理解。适用于角色识别、图片描述、风格分析、截图理解等任务。
使用说明 (SKILL.md)

local-gmncode-vision

当你发现:

  • image 工具报错
  • 错误包含 No media-understanding provider registered
  • 当前环境已有 GMNCODE_API_KEY

就用这个技能。

用法

脚本路径: /home/ubuntu/.openclaw/workspace/scripts_gmncode_image.py

基础调用:

/home/ubuntu/.openclaw/workspace/scripts_gmncode_image.py \x3Cimage_path> "你的提示词"

示例:

/home/ubuntu/.openclaw/workspace/scripts_gmncode_image.py /path/to/image.jpg "识别这张图里的角色;如果无法确认具体角色,就描述人物外观、服饰和可能风格来源。"

适用场景

  • 识别二次元/国漫/游戏角色
  • 描述人物外观、服装、风格
  • 分析截图界面内容
  • 在官方 image 工具失效时提供稳定替代

注意事项

  • 依赖环境变量:GMNCODE_API_KEY
  • 当前默认模型:gpt-5.4
  • 这是本地替代方案,不是 OpenClaw 官方 image provider 修复
  • 如果后续官方 image 工具修好,优先用官方工具

输出原则

  • 不确定时明确说“不确定”
  • 可以给出“更像谁”的概率判断
  • 不要把风格像误说成实锤出处
安全使用建议
Do not run or grant secrets for this skill until you or the publisher supply and you review the referenced script (/home/ubuntu/.openclaw/workspace/scripts_gmncode_image.py). Specifically: (1) Inspect the script source to confirm what network endpoints it calls, what data it sends, and whether it logs or transmits your files or environment variables. (2) Confirm why the package metadata omitted GMNCODE_API_KEY and request that the skill declare required env vars and include or link the script source. (3) If you must test, use a limited-scope or disposable GMNCODE_API_KEY and run in an isolated environment. (4) Prefer the official image provider when available and rotate or revoke any key used for testing. If the publisher cannot provide the script source or a trustworthy explanation, treat the skill as untrusted.
功能分析
Type: OpenClaw Skill Name: local-gmncode-vision Version: 1.0.0 The skill bundle provides instructions for the agent to execute a local Python script (`scripts_gmncode_image.py`) at a hardcoded path to handle image processing. However, the source code for this script is not included in the bundle, meaning the agent is being directed to run an unverified local payload. Additionally, the documentation references a non-existent model version ('gpt-5.4'), which is anomalous. While the stated purpose is a benign fallback for image recognition, the lack of transparency regarding the executed code warrants a suspicious classification.
能力评估
Purpose & Capability
The SKILL.md says the skill is a local fallback that directly calls the GMNCODE Responses API and depends on GMNCODE_API_KEY, which is coherent with the described purpose. However, the package metadata lists no required environment variables and no primary credential, and the actual helper script (/home/ubuntu/.openclaw/workspace/scripts_gmncode_image.py) is not included in the skill bundle. The missing declaration of the API key and the absent script file are inconsistencies.
Instruction Scope
Runtime instructions explicitly tell the agent to run an absolute-path local script. Because the skill bundle does not include that script, the agent would execute an external, unseen file on disk. The instructions rely on the GMNCODE_API_KEY env var and on network access to an external API (implied), but provide no details about what the script does or what data it sends/receives.
Install Mechanism
There is no install spec and no code files in the bundle (instruction-only), so the skill itself does not place new binaries on disk. That lowers supply-chain risk. However, the skill's value depends on a separate local script outside the bundle, which raises operational risk because that external script is unreviewed.
Credentials
The instructions declare a dependency on GMNCODE_API_KEY (sensitive credential) but the skill's declared requirements list no environment variables and no primary credential — an evident mismatch. Requesting an API key for the stated purpose is reasonable, but the lack of metadata and lack of included script means you cannot verify how that key would be used or where data might be sent.
Persistence & Privilege
The skill is not marked always:true and does not request persistent installation or system-wide config changes. It is user-invocable only. Autonomous invocation is allowed by default but is not combined here with other elevated privileges.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install local-gmncode-vision
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /local-gmncode-vision 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: GMNCODE-based local image understanding fallback when built-in image tool is unavailable.
元数据
Slug local-gmncode-vision
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Local GMNCODE Vision 是什么?

当内置 image 工具不可用、但本机配置了 GMNCODE_API_KEY 时,使用本地脚本直连 GMNCODE Responses API 完成图片理解。适用于角色识别、图片描述、风格分析、截图理解等任务。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 110 次。

如何安装 Local GMNCODE Vision?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install local-gmncode-vision」即可一键安装,无需额外配置。

Local GMNCODE Vision 是免费的吗?

是的,Local GMNCODE Vision 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Local GMNCODE Vision 支持哪些平台?

Local GMNCODE Vision 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Local GMNCODE Vision?

由 iO2077(@io2077)开发并维护,当前版本 v1.0.0。

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