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ringorangers

我的测试

by RingoRangers · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
261
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1
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0
Active Installs
1
Versions
Install in OpenClaw
/install test-outbound
Description
登录外呼系统并调用 save_session.py 保存浏览器会话到 auth.json。用于首次登录、会话失效或开始任务前重新准备登录态。
Usage Guidance
Before installing or running this skill: - Do not run anything until you have the actual save_session.py script from a trusted source. The registry package does not include it. - Inspect save_session.py (and any code you obtain) carefully to ensure it does not send auth.json or credentials to external endpoints. - Prefer providing credentials via a secure secrets mechanism rather than a plaintext login_credentials.json file; if you must use a file, restrict filesystem permissions and remove it after use. - Treat auth.json as highly sensitive: store it securely, limit access, and rotate credentials if it may have been exposed. - If you cannot review the script, consider creating a throwaway/test account to run the process first so long-lived credentials are not exposed. - If you need the skill to be fully self-contained, request the publisher include save_session.py and a clear README describing exactly what the script does and any network endpoints it communicates with.
Capability Analysis
Type: OpenClaw Skill Name: test-outbound Version: 1.0.0 The skill is designed to handle sensitive authentication data, including plaintext credentials (login_credentials.json) and browser session tokens (auth.json), which are high-value targets for exfiltration. It relies on an external script, save_session.py (the content of which was not provided for review), to automate login via Playwright. While the documentation describes a legitimate automation use case for an 'outbound system,' the management of authentication secrets and the lack of visibility into the script's logic present a significant security risk.
Capability Assessment
Purpose & Capability
The description says the skill runs save_session.py to produce auth.json. However, no code files are included (no save_session.py). That makes the skill non-functional as delivered and requires the user to supply or obtain an external script. Requiring a separate script is not inherently malicious, but the absence is an important incoherence: the skill cannot do what it claims without an external artifact that the package does not provide or vouch for.
Instruction Scope
SKILL.md instructs the agent/user to prepare login_credentials.json and run python3 save_session.py which will open a browser, autofill credentials, and save auth.json. These steps are consistent with the stated purpose, but they involve handling highly sensitive data (account credentials and session cookies). The instructions do not specify where save_session.py should come from, what it does exactly, or any safeguards for storing/transmitting auth.json. There are no instructions that send data to external endpoints, but because the referenced script is absent, its behavior is unknown and could include exfiltration if obtained from an untrusted source.
Install Mechanism
No install spec is included (instruction-only skill). The README notes pip-installing Playwright and installing Chromium, which is appropriate for a Playwright-based session saver. Because nothing is downloaded or installed by the skill bundle itself, there is no immediate install-time risk from the registry package, but the user still must install third-party software manually.
Credentials
The skill declares no required environment variables and no primary credential, which is proportionate. However, it relies on a credentials file (login_credentials.json) provided by the user and produces auth.json containing cookies/session tokens — both sensitive. Storing credentials in a file (instead of ephemeral secrets) increases risk; the skill does not provide guidance on secure storage or access controls.
Persistence & Privilege
always is false and the skill does not request persistent presence or modify other skills. Autonomous model invocation is allowed by default but not combined with any other privilege escalation indicators here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install test-outbound
  3. After installation, invoke the skill by name or use /test-outbound
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of the outbound-login skill. - Enables logging into the outbound call system and saving browser session to auth.json for later use. - Guides users to prepare login credentials and manually handle captcha during login. - save_session.py automates most of the login workflow except for captcha input. - Requires Playwright and Chromium to be installed in the environment. - Outputs session data as auth.json for downstream tasks.
Metadata
Slug test-outbound
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is 我的测试?

登录外呼系统并调用 save_session.py 保存浏览器会话到 auth.json。用于首次登录、会话失效或开始任务前重新准备登录态。 It is an AI Agent Skill for Claude Code / OpenClaw, with 261 downloads so far.

How do I install 我的测试?

Run "/install test-outbound" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is 我的测试 free?

Yes, 我的测试 is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does 我的测试 support?

我的测试 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created 我的测试?

It is built and maintained by RingoRangers (@ringorangers); the current version is v1.0.0.

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