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Financial Times Deep Reader

作者 zhouziyue233 · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
693
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install ft-reader
功能描述
Automates login to FT.com to extract and provide detailed bilingual English-Chinese summaries of top Financial Times articles with academic rigor.
使用说明 (SKILL.md)

Financial Times Deep Reader (ft-reader)

Use this skill to perform deep, structured, and bilingual analysis of top articles from Financial Times (ft.com). This skill automates login, article selection, and high-quality summarization suitable for academic and professional use.

Capabilities

  • Automated Access: Logs into FT.com using stored credentials via Browser tool.
  • Strategic Selection: Identifies "Most Read" based on user preference.
  • Bilingual Synthesis: Provides high-fidelity English-Chinese summaries with a focus on core arguments.
  • Academic Rigor: Extracts specific data, quotes, and important charts in the article.

Configuration & Credentials

  • Browser Profile: Use openclaw profile to maintain session persistence.
  • Credentials:
    • User: xxxxxx
    • Pass: xxxxxx

Workflow (Mandatory Steps)

Phase 1: Authentication & Navigation

  1. Open https://www.ft.com/login.
  2. Enter email and password.
  3. Navigate to the homepage or a specific section requested by the user.

Phase 2: Content Extraction

  1. Use evaluate to identify the top N articles from the homepage (targeting .o-teaser__heading or most-read sections).

  2. For each target article:

    • Navigate to the article URL.

    • Use evaluate with the following JavaScript to extract clean content:

      () => {
        const title = document.querySelector('h1')?.innerText;
        const standfirst = document.querySelector('div[class*="standfirst"]')?.innerText;
        const paragraphs = Array.from(document.querySelectorAll('div[class*="article-body"] p, article p'))
          .map(p => p.innerText.trim())
          .filter(text => text.length > 0);
        return { title, summary: standfirst, content: paragraphs.join('\
      


') }; } ```

Phase 3: Analysis & Reporting

For each article, generate a report (around 600 words) using the following structure:

  • Title (Bilingual)
  • Core Opinion (Bilingual)
  • Arguments (Bilingual)
  • Conclusion (Bilingual)

Constraints

  • Style: Professional, academic, and fluff-free (follow SOUL.md).
  • Language: Always provide both English and Chinese translations for technical terms and core ideas.
  • Independent Reading: Treat each article as a standalone piece unless cross-analysis is requested.
  • Token Management: If many articles are requested, split the delivery into multiple turns to avoid truncation.

Usage Examples

  • "Lulu, use ft-reader to analyze the top 3 Most Read articles from today."
  • "Perform a deep dive into the top story on FT regarding AI productivity using the ft-reader skill."
安全使用建议
This skill is suspicious because its runtime instructions require login credentials and use of a specific browser profile, but the registry metadata does not declare any credentials or configuration paths. Before installing or enabling it: 1) Ask the publisher for source code or a homepage and for a clear explanation of where credentials should be stored and how they are protected (prefer OAuth or token-based flows over plaintext credentials). 2) Do not enter your FT account email/password unless you fully trust the publisher; prefer using an account with no subscriptions or a throwaway account for testing. 3) Ask whether the skill will access your local browser profile or cookies; if so, decline unless you understand exactly what data will be read and why. 4) Confirm legal/ToS implications of scraping paywalled content. 5) If you must test, run it in a restricted environment (isolated profile or VM) and monitor network traffic. Providing a trusted source repo, explicit required env var names, or an OAuth-based integration would increase confidence and could change this assessment.
功能分析
Type: OpenClaw Skill Name: ft-reader Version: 1.0.0 The skill bundle is classified as benign. The `SKILL.md` provides clear instructions for the OpenClaw agent to log into Financial Times and extract article content using the `Browser` tool. The embedded JavaScript for content extraction is limited to reading DOM elements and does not attempt to access sensitive browser data, make unauthorized network requests, or perform any malicious actions. There is no evidence of prompt injection, data exfiltration, or other harmful behaviors.
能力评估
Purpose & Capability
The skill's purpose is to log into FT.com and extract articles — that legitimately requires credentials or session access. However, the registry lists no required environment variables, no primary credential, and no required config paths, while SKILL.md explicitly instructs use of a Browser profile named 'openclaw' and to enter email/password. This mismatch (claims of automated login vs. no declared credential/config requirements) is incoherent and raises risk about where credentials would come from and how they would be accessed.
Instruction Scope
SKILL.md instructs the agent to navigate to FT login pages, enter email/password, and run page-evaluation JavaScript to extract article text — these actions are consistent with the stated functionality. However, the instructions also demand use of a named browser profile ('openclaw') to maintain session persistence and include placeholder credentials in the file, without describing the source/secure storage of those credentials. That gives the skill broad discretion to access browser session data and credentials not declared to the registry, which is outside what a safe, self-contained instruction-only skill should assume. Also note potential legal/ToS concerns about automated scraping of paywalled content; the skill does not mention compliance.
Install Mechanism
There is no install spec and no code files — the skill is instruction-only. This minimizes filesystem risk because nothing is downloaded or written during install. The lack of an install step also explains why there are no declared dependencies, but it does not resolve the credential/access inconsistencies.
Credentials
The skill needs login credentials and persistent browser session access to function, yet the registry lists no required env vars, no primary credential, and no config paths. Requiring access to a browser profile (which can contain cookies, tokens, and other site credentials) is a high-privilege action; it should be explicitly declared and justified. The omission of any declared credential or config requirements is disproportionate and ambiguous.
Persistence & Privilege
The skill is not set to always:true and does not request persistent installation. Autonomous invocation is allowed (the platform default). Combined with the credential/session access the SKILL.md asks for, autonomous runs could access stored browser sessions or prompt for credentials without clear registry-level controls — this increases the blast radius but is not itself a configuration flag set by the skill.
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 ft-reader
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /ft-reader 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
v1.0.0
Financial Times Deep Reader (ft-reader) 1.0.0 - Initial release enabling automated, structured analysis of Financial Times articles. - Supports login and navigation using secure browser profile and credentials. - Extracts top "Most Read" articles as per user preference. - Produces bilingual (English-Chinese) summaries with academic rigor, including key arguments, data, and quotes. - Delivers detailed reports in a professional, concise format, suitable for academic and professional use.
元数据
Slug ft-reader
版本 1.0.0
许可证
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Financial Times Deep Reader 是什么?

Automates login to FT.com to extract and provide detailed bilingual English-Chinese summaries of top Financial Times articles with academic rigor. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 693 次。

如何安装 Financial Times Deep Reader?

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

Financial Times Deep Reader 是免费的吗?

是的,Financial Times Deep Reader 完全免费(开源免费),可自由下载、安装和使用。

Financial Times Deep Reader 支持哪些平台?

Financial Times Deep Reader 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 Financial Times Deep Reader?

由 zhouziyue233(@zhouziyue233)开发并维护,当前版本 v1.0.0。

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