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Reward Sciences
作者
Vlad Ursul
· GitHub ↗
· v1.0.3
· MIT-0
231
总下载
0
收藏
0
当前安装
4
版本数
在 OpenClaw 中安装
/install reward-sciences
功能描述
Reward Sciences integration. Manage Persons, Organizations, Deals, Leads, Projects, Activities and more. Use when the user wants to interact with Reward Scie...
安全使用建议
This skill appears coherent and does what it says: it relies on the Membrane CLI to broker access to Reward Sciences. Before installing/using it, consider: 1) Vet the @membranehq/cli package and its publisher (npm page, repo, recent activity, reviews) before installing globally; use the provided npx examples if you prefer not to install globally. 2) Understand that you are delegating credential management to Membrane — review their privacy/security practices and terms. 3) In headless environments you'll need to perform the OAuth browser step (obtain and paste the code) — avoid pasting codes from untrusted sources. 4) Because the skill requires network access and a Membrane account, ensure your environment/network policies permit that outbound access. If you need more assurance, provide the package name and repository URL and verify its source code before installing.
功能分析
Type: OpenClaw Skill
Name: reward-sciences
Version: 1.0.3
The skill bundle (SKILL.md) instructs the agent to perform high-risk system operations, including installing a global NPM package (@membranehq/cli) and executing shell commands to manage authentication and data via the Membrane platform. While these actions are aligned with the stated purpose of integrating with Reward Sciences, the requirement for global package installation and the execution of external binaries (membrane CLI) without local source code visibility constitutes a significant risk profile and potential attack surface.
能力评估
Purpose & Capability
Name/description match the runtime instructions: the SKILL.md describes interacting with Reward Sciences via the Membrane CLI, creating connections, listing/creating actions, and running them. Nothing requested (no env vars, no config paths) is unrelated to this purpose.
Instruction Scope
Instructions are scoped to using the Membrane CLI (login, connect, action list/create/run). They do not instruct reading arbitrary local files, exporting unexpected data, or accessing unrelated credentials. Headless login flow requires the user to paste a code, which is normal for CLI OAuth flows.
Install Mechanism
The SKILL.md recommends installing @membranehq/cli globally via npm (or using npx in one example). There is no install spec in the manifest (instruction-only skill). Installing a global npm package writes to the system and requires trusting that package/publisher; this is expected for a CLI-based integration but users should vet the package and prefer npx when possible.
Credentials
The skill declares no required environment variables or credentials and explicitly advises not to ask users for API keys (Membrane manages auth server-side). The only external requirement is a Membrane account and network access, which is proportionate to the described functionality.
Persistence & Privilege
always is false and there are no instructions to modify other skills or global agent configs. The skill does not request persistent system privileges beyond using the Membrane CLI when installed by the user.
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 reward-sciences - 安装完成后,直接呼叫该 Skill 的名称或使用
/reward-sciences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
Auto sync from membranedev/application-skills
v1.0.2
Revert refresh marker
v1.0.1
Refresh update marker
v1.0.0
Auto sync from membranedev/application-skills
元数据
常见问题
Reward Sciences 是什么?
Reward Sciences integration. Manage Persons, Organizations, Deals, Leads, Projects, Activities and more. Use when the user wants to interact with Reward Scie... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 231 次。
如何安装 Reward Sciences?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install reward-sciences」即可一键安装,无需额外配置。
Reward Sciences 是免费的吗?
是的,Reward Sciences 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Reward Sciences 支持哪些平台?
Reward Sciences 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 Reward Sciences?
由 Vlad Ursul(@gora050)开发并维护,当前版本 v1.0.3。
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