← 返回 Skills 市场
helloeveryworlds

News Trust Check

作者 helloeveryworlds · GitHub ↗ · v0.1.1 · MIT-0
cross-platform ⚠ suspicious
312
总下载
1
收藏
1
当前安装
2
版本数
在 OpenClaw 中安装
/install news-trust-check
功能描述
Verify suspicious news, announcements, screenshots, and viral claims using a high-trust source pool (official channels + Chinese mainstream media + internati...
安全使用建议
This skill appears coherent and low-risk: it contains only an instruction document, a trusted-source list, and a small local Python script that scores text by keyword. Before installing, consider: (1) whether you want the agent to have network access when it "queries" sources (the skill assumes the agent can fetch news/fact-check pages); (2) the trusted-source list reflects editorial choices—verify it matches sources you trust; and (3) review operator policies if you need to restrict autonomous web queries. If you are comfortable with the agent performing web lookups, this skill's footprint is proportionate to its purpose.
功能分析
Type: OpenClaw Skill Name: news-trust-check Version: 0.1.1 The skill is a news verification and scam-detection tool designed to help users evaluate the credibility of claims. It includes a Python script (scripts/assess_claim.py) that performs basic keyword-based risk scoring for common phishing indicators (e.g., 'token', 'password', 'transfer') and a reference list of high-trust media sources. The instructions in SKILL.md specifically include defensive measures to identify and flag prompt-injection attempts ('ignore all rules') and social engineering, aligning perfectly with its stated purpose without any high-risk behaviors.
能力评估
Purpose & Capability
Name/description match the contents: SKILL.md describes a cross-check workflow, references list trusted outlets, and a small local script scores claims for risky keywords. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Runtime instructions stick to claim extraction, source cross-checking, feasibility checks, and structured output. The guidance to "query" official and mainstream sources is expected for this task; the skill does not embed broad directives to read unrelated local files or secrets. The Danger short-circuit and risk indicators explicitly flag prompt-injection style coercion (e.g., "ignore all rules"), which is consistent with the skill's purpose.
Install Mechanism
No install spec; instruction-only plus a small Python helper script. Nothing is downloaded from external URLs and no archives are extracted.
Credentials
The skill requests no environment variables, credentials, or config paths. The helper script performs local string matching only and does not access network resources or secrets.
Persistence & Privilege
always is false and the skill does not request persistent elevated privileges or modify other skills. Autonomous invocation is allowed by default (normal) and is not combined with other concerning factors.
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 news-trust-check
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /news-trust-check 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
v0.1.1
Improve reliability: add empty-input validation and consistent error exit behavior in scoring helper script.
v0.1.0
Initial release: rumor verification workflow with high-trust CN+global source pool, technical-feasibility check, risk short-circuit rules, and structured verdict template.
元数据
Slug news-trust-check
版本 0.1.1
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 2
常见问题

News Trust Check 是什么?

Verify suspicious news, announcements, screenshots, and viral claims using a high-trust source pool (official channels + Chinese mainstream media + internati... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 312 次。

如何安装 News Trust Check?

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

News Trust Check 是免费的吗?

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

News Trust Check 支持哪些平台?

News Trust Check 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 News Trust Check?

由 helloeveryworlds(@helloeveryworlds)开发并维护,当前版本 v0.1.1。

💬 留言讨论