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购物省钱攻略
作者
GeraldAlexanderrw
· GitHub ↗
· v1.0.3
· MIT-0
200
总下载
0
收藏
0
当前安装
4
版本数
在 OpenClaw 中安装
/install shopping-helper
功能描述
购物省钱攻略,当用户询问网购、购物、买东西、划算时调用。
安全使用建议
This skill appears to do what it claims (fetch and show coupons) and is not trying to access unrelated credentials or system files. However: (1) the bundled script includes hardcoded API credentials and a fixed remote endpoint — review whether you trust that endpoint and the embedded keys; (2) the script makes outbound POST requests and will contact that remote service (network activity and potential tracking); (3) it writes a cache file to /tmp and can invoke the 'clawhub' CLI for updates if present. If you plan to install, consider asking the publisher for the source/homepage, verifying the aggregator (open.datadex.com.cn), or requesting removal of embedded keys so credentials aren't baked into the skill. If you cannot verify the endpoint, avoid installing or run the skill in an environment that restricts outbound network access.
功能分析
Type: OpenClaw Skill
Name: shopping-helper
Version: 1.0.3
The skill includes a self-update mechanism in `scripts/get_coupon.py` that executes system commands (`clawhub update`) via `subprocess.run`. This behavior is explicitly triggered by instructions in `SKILL.md` that direct the AI agent to suggest an 'upgrade' command to the user if errors occur. While documented as a maintenance feature, the ability for a skill to invoke external package managers to modify itself is a high-risk capability. Additionally, the script contains hardcoded affiliate referral strings (淘口令) in its fallback data, indicating a monetization motive common in grayware.
能力评估
Purpose & Capability
The name/description (shopping coupon aggregator) aligns with the actual behavior: the Python script requests coupon data from an external aggregator, filters categories/coupons, caches results, and prints output. No unrelated capabilities (cloud admin, filesystem scanning beyond a single cache file, or unrelated service access) are present.
Instruction Scope
SKILL.md and the script stay within the shopping/coupon domain. The runtime instructions and code only read/write a local cache (/tmp/coupon_data_cache), call a third‑party API endpoint, and implement an update command. There are no instructions to read arbitrary user files, environment secrets, or system configuration beyond the cache and a declared skill path variable (not used).
Install Mechanism
This is an instruction-only skill with a bundled script and no install spec. Nothing in the repository triggers downloading or extracting arbitrary archives. The only external command invoked (if used) is a local 'clawhub update' for upgrades; that is a normal update mechanism but will perform network activity if clawhub is present.
Credentials
The package declares no required env vars, but the Python script contains hardcoded third‑party API credentials (a1/a2) and a fixed API URL (open.datadex.com.cn). Hardcoded keys in source are poor security hygiene and mean the skill will send these credentials to the remote service. The skill does not request unrelated credentials, but embedding secrets in code is worth flagging.
Persistence & Privilege
The skill is not always-enabled and does not request persistent platform privileges. It does write a cache to /tmp and suggests running an update via 'clawhub', but it does not modify other skills or system settings.
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 shopping-helper - 安装完成后,直接呼叫该 Skill 的名称或使用
/shopping-helper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
v1.0.3
恢复预置凭证,开箱即用
v1.0.2
移除真实凭证,改为要求用户配置环境变量,明确披露所有配置项
v1.0.1
移除base64混淆,改用环境变量配置凭证
v1.0.0
专注网购场景,覆盖京东淘宝拼多多等平台
元数据
常见问题
购物省钱攻略 是什么?
购物省钱攻略,当用户询问网购、购物、买东西、划算时调用。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 200 次。
如何安装 购物省钱攻略?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install shopping-helper」即可一键安装,无需额外配置。
购物省钱攻略 是免费的吗?
是的,购物省钱攻略 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
购物省钱攻略 支持哪些平台?
购物省钱攻略 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 购物省钱攻略?
由 GeraldAlexanderrw(@geraldalexanderrw)开发并维护,当前版本 v1.0.3。
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