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Multi-panel Figure Assembler

作者 AIpoch · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
112
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install multi-panel-figure-assembler
功能描述
Assemble 6 sub-figures (A–F) into a high-resolution composite figure with consistent labels, padding, and publication-ready DPI.
安全使用建议
This skill appears coherent and implements exactly what it claims: assembling six image panels into a composite using local Python code. Before running, consider these practical precautions: (1) Review the included scripts (scripts/main.py and scripts/example.py) yourself — they will execute on your machine. (2) Run in an isolated environment (virtualenv or container) and install dependencies (pip install Pillow numpy); note requirements.txt contains a redundant/incorrect 'pil' entry — install 'Pillow' instead. (3) Use python -m py_compile scripts/main.py and run the --help to confirm expected behavior; the SKILL.md already suggests these checks. (4) Verify font fallbacks and that input paths are correct; the code already rejects ../ traversal. (5) Do not run as root and avoid executing third-party code on sensitive hosts without review. If you want higher assurance, run the example outputs in a sandbox and inspect the saved images before using in production.
功能分析
Type: OpenClaw Skill Name: multi-panel-figure-assembler Version: 1.0.0 The skill is a legitimate utility for assembling image grids using the Pillow and NumPy libraries. The code in scripts/main.py is well-structured, lacks dangerous functions (like eval or subprocess), and performs standard image processing tasks. The SKILL.md documentation includes proactive security measures, such as explicit instructions for the agent to check for path traversal (../) and strictly enforce input validation to prevent scope creep or prompt injection.
能力评估
Purpose & Capability
The name/description describe assembling 6 panels into a composite figure; the included Python scripts (Pillow + numpy) implement exactly that functionality. Declared dependencies and example commands match the stated purpose; there are no unrelated environment variables, binaries, or external service credentials requested.
Instruction Scope
SKILL.md enforces a strict hard gate (exactly 6 panels) and documents local-only behavior (file load, resizing, labeling, saving). It explicitly forbids path traversal and out-of-scope operations, gives clear error/fallback templates, and only references local file system operations and font paths; there are no instructions to call external endpoints or read unrelated system secrets.
Install Mechanism
No install spec is provided (instruction-only), which reduces supply-chain risk — the skill will run the packaged Python code. The SKILL.md recommends 'pip install Pillow numpy' (appropriate). Small packaging issues: requirements.txt lists both 'pil' and 'pillow' (the 'pil' entry is incorrect/redundant); this is a minor quality issue, not a coherence/security problem.
Credentials
The skill requests no environment variables, credentials, or config paths. The functionality (image assembly) does not require secrets or cloud credentials, so the lack of requested secrets is appropriate.
Persistence & Privilege
always: false and no special persistence is requested. The skill does not modify other skills or global agent settings. Autonomous invocation is allowed by platform default but is not combined with any broad privileges or secret access.
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 multi-panel-figure-assembler
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /multi-panel-figure-assembler 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 public release: assemble exactly 6 sub-figures (A–F) into a publication-ready composite figure. - Validates that exactly 6 image panels and an output path are provided; strictly refuses out-of-scope tasks. - Supports 2×3 or 3×2 grid layouts, high-DPI output, label font customization, and consistent padding/borders. - Wide format compatibility: input PNG/JPEG/TIFF/BMP/GIF, output PNG/JPEG/TIFF. - Robust error handling with explicit fallback template and input safety checks. - Output is standardized with consistent labels, panel resizing, and publication-ready settings.
元数据
Slug multi-panel-figure-assembler
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

Multi-panel Figure Assembler 是什么?

Assemble 6 sub-figures (A–F) into a high-resolution composite figure with consistent labels, padding, and publication-ready DPI. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 112 次。

如何安装 Multi-panel Figure Assembler?

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

Multi-panel Figure Assembler 是免费的吗?

是的,Multi-panel Figure Assembler 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Multi-panel Figure Assembler 支持哪些平台?

Multi-panel Figure Assembler 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 Multi-panel Figure Assembler?

由 AIpoch(@aipoch-ai)开发并维护,当前版本 v1.0.0。

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