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Sticker Manager

作者 zhuwenzhuang · GitHub ↗ · v0.3.0 · MIT-0
cross-platform ⚠ suspicious
141
总下载
1
收藏
1
当前安装
4
版本数
在 OpenClaw 中安装
/install sticker-manager
功能描述
Sticker library management for OpenClaw. Use this skill to save, search, tag, rename, clean up, collect, import, and recommend stickers or reaction images. I...
安全使用建议
This skill appears to be what it claims: a local sticker manager implemented as Python scripts. Before installing or running it, consider: 1) It will read from and write to your local sticker library and inbound media directories (defaults under ~/.openclaw); set STICKER_MANAGER_DIR and STICKER_MANAGER_INBOUND_DIR to an isolated folder if you want to limit impact. 2) The collector/discovery commands will make HTTP requests to URLs you provide — only supply trusted sources. 3) Vision/auto-tag features produce plans referencing external models (e.g., openai/gpt-5-mini) but do not include or ask for API keys; enabling automated vision/model execution requires separate model/tool credentials and integration. 4) If you want extra safety, review the scripts (they are included) and run them in a sandbox or dedicated user account; run the provided tests and the included check_sensitive.py before publishing changes.
功能分析
Type: OpenClaw Skill Name: sticker-manager Version: 0.3.0 The sticker-manager skill is a comprehensive tool for managing local sticker libraries, supporting operations like saving, searching, semantic tagging, and batch importing. It includes a developer-focused security script (check_sensitive.py) designed to prevent the accidental commitment of secrets like API keys or private paths. Network functionality in scripts like collect_stickers.py and discover_sources.py is strictly aligned with the stated purpose of fetching and discovering image assets, and the code follows standard OpenClaw patterns for multi-step reasoning and vision-model integration without any evidence of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The repository contents (save, search, rename, batch import/collect, semantic/vision plan scripts) match the declared purpose of local sticker library management. Required artifacts (local library, inbound media) and supported formats are coherent with the features. There are no unexpected credentials or unrelated system dependencies in the manifest.
Instruction Scope
SKILL.md and scripts instruct the agent to read/write the default library (~/.openclaw/workspace/stickers/library/) and inbound media (~/.openclaw/media/inbound/) and to run included Python scripts. Several commands optionally perform network fetches (collect/discover) to user-provided URLs and prepare vision-model payloads for external model execution. These actions are consistent with the stated functionality but do require filesystem access and (for collection) outgoing HTTP requests — which is expected but worth noting.
Install Mechanism
There is no install spec and the repo is instruction-plus-scripts (Python). No downloads from arbitrary URLs or packaged executables are requested. The requirements.txt lists common packages (requests, Pillow, pytest) appropriate for the code. No high-risk install steps (URL downloads/extracts) are present in the provided files.
Credentials
The skill uses environment variables documented in SKILL.md (STICKER_MANAGER_DIR, STICKER_MANAGER_INBOUND_DIR, STICKER_MANAGER_LANG, STICKER_MANAGER_VISION_MODELS). It does not request API keys or other secrets. It references model identifiers (e.g., openai/gpt-5-mini) for vision fallback plans but does not include or require credentials — executing those model steps requires external model/tool credentials which are intentionally left to the outer agent/tooling, consistent with the README.
Persistence & Privilege
The skill is not marked always:true and does not request persistent platform privileges. It reads/writes only within defined local paths (or paths supplied by the user) and does not modify other skills' configurations. Autonomous invocation is the platform default and is not combined with other red flags.
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 sticker-manager
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /sticker-manager 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
v0.3.0
Animation preservation: generic rule, GIPHY support, reject static fallbacks for animated sources
v0.2.2
Add GitHub repository link as fallback download source when ClawHub is unavailable.
v0.2.1
Release polish: add requests dependency, Makefile, stronger hooks/CI parity, better SKILL/README alignment, and safer CLI help behavior.
v0.1.0
Initial release: save, search, tag, recommend stickers
元数据
Slug sticker-manager
版本 0.3.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 4
常见问题

Sticker Manager 是什么?

Sticker library management for OpenClaw. Use this skill to save, search, tag, rename, clean up, collect, import, and recommend stickers or reaction images. I... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 141 次。

如何安装 Sticker Manager?

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

Sticker Manager 是免费的吗?

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

Sticker Manager 支持哪些平台?

Sticker Manager 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 Sticker Manager?

由 zhuwenzhuang(@zhuwenzhuang)开发并维护,当前版本 v0.3.0。

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