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在 OpenClaw 中安装
/install paper-architecture-diagram
功能描述
自动化处理本地医学图像分割论文，提取结构解析与绘图提示，严格按步骤保存结果至指定文本文件。
安全使用建议
Before installing or running this skill, consider the following:
- Privacy: the skill instructs uploading a local PDF (medical imaging paper) to Gemini (an external model/service). If the paper contains sensitive patient data or confidential research, do not upload it without appropriate consent and data‑handling controls.
- Hard-coded path: the skill uses /home/xie/桌面/... for both input and output. If your files are elsewhere the skill will fail or may attempt to access unrelated files. Ask the author to parameterize the base directories or confirm the intended host.
- Forced behavior: the SKILL.md forbids ending the task unless the agent successfully writes the output file and forbids printing results before writing. This can cause repeated uploads, long-running loops, or unexpected file writes—test carefully with a non-sensitive dummy PDF first.
- Access required: the skill needs MCP browser/file-upload and MCP file-write capabilities enabled. Review what MCP will actually do (network upload, write to your filesystem) and ensure you trust the endpoint.
- If you need to proceed: run a controlled test (dummy paper) and verify exactly what data is sent to Gemini and what ends up in /home/youruser/desktop/analysis/. If the skill is intended for general distribution, ask the maintainer to remove hard-coded paths, document privacy implications, and add explicit consent and configurable paths.
If you can provide more context—who operates /home/xie on the target machine, whether Gemini Pro is an approved service for your data, or whether the tool should run entirely locally—I can raise or lower the confidence and refine the advice.
功能分析
Type: OpenClaw Skill
Name: paper-architecture-diagram
Version: 1.0.0
The skill automates uploading local PDF files to Gemini and saving results to the local filesystem using hardcoded paths (/home/xie/桌面/). It is classified as suspicious due to a potential path traversal vulnerability in the 'paper_name' parameter, which is used to construct file paths without sanitization, potentially allowing unauthorized file access. Additionally, SKILL.md employs aggressive prompt engineering and 'meta-instructions' to override the agent's default behavior and force specific tool executions, which mimics prompt-injection techniques.
能力评估
Purpose & Capability
The name/description (extract diagrams/prompts from local medical papers and save to a local file) aligns with the instructions and the declared mcp capability in config.yaml. However, the SKILL.md hard-codes the local paths to /home/xie/..., which is specific to a particular user environment and not generally appropriate. Requiring Gemini (external service) and MCP browser/file-write are plausible for the stated purpose but the hard-coded path reduces portability and suggests the skill was authored for a single host.
Instruction Scope
Instructions explicitly demand uploading a local medical paper to Gemini via MCP browser-file-upload and prohibit outputting parsed results until the skill writes them to disk. Uploading possibly sensitive medical PDFs to an external model/service is a privacy risk. The instructions also force procedural constraints (never end unless step 7 writes file, forbid printing intermediate results) that can cause the agent to insist on writing to disk or loop until the write succeeds. The requirement to use browser-file-upload rather than other UI actions is unusually prescriptive but consistent with automated file transfer—still it increases the chance of exfiltration to an external service.
Install Mechanism
Instruction-only skill with no install steps and no additional binaries or packages declared. From an install-mechanism viewpoint this is low-risk—nothing is written to disk by an installer and there are no download URLs.
Credentials
The skill requests no environment variables or credentials, which is appropriate. However, it requires access to specific local filesystem paths (/home/xie/桌面/...), which is a form of privileged local access: the skill will read a local PDF and write an output file. For medical data this is a meaningful sensitivity concern. The fixed home path is disproportionate for a general skill and may indicate it was designed for a single user's environment rather than general use.
Persistence & Privilege
The skill does not request always:true and does not modify other skills/configs. It does require using MCP to write a local file (normal for a tool that saves results). The coercive requirement 'task not complete until file written' and the ban on outputting results before write are unusual and can cause the agent to continue operating until the file write succeeds; this increases operational/risk surface (loops, repeated uploads) but is not itself an elevation of privilege.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install paper-architecture-diagram - 安装完成后，直接呼叫该 Skill 的名称或使用
/paper-architecture-diagram触发 - 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 of the paper-architecture-diagram skill.
- Strict step-by-step workflow for parsing medical image segmentation papers and generating diagram prompts.
- Enforces file upload, prompt input, and result extraction strictly via MCP browser automation.
- Adds critical rules to ensure only successful file writing marks task completion; prohibits skipping or ending at intermediate steps.
- Clearly defines local file paths for input and output; all processing is performed locally and tracked stepwise.
元数据
常见问题
paper-architecture-diagram 是什么？
自动化处理本地医学图像分割论文，提取结构解析与绘图提示，严格按步骤保存结果至指定文本文件。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 77 次。
如何安装 paper-architecture-diagram？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install paper-architecture-diagram」即可一键安装，无需额外配置。
paper-architecture-diagram 是免费的吗？
是的，paper-architecture-diagram 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
paper-architecture-diagram 支持哪些平台？
paper-architecture-diagram 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 paper-architecture-diagram？
由 m1ss-cell（@m1ss-cell）开发并维护，当前版本 v1.0.0。
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