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Web Fetcher

作者 Aurthes · GitHub ↗ · v1.2.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install aurthes-web-fetcher
功能描述
Fetch web pages and extract readable content for AI use. Use when reading, summarizing, or crawling a specific URL or small set of URLs. Prefer low-friction...
使用说明 (SKILL.md)

Web Fetcher

Fetch readable web content with a reliability-first fallback chain.

Core rule

Do not promise direct access to every site. Some sites use Cloudflare, login walls, bot detection, or legal restrictions. In those cases, switch to the next fallback instead of insisting the first method should work.

Preferred fetch order

1) Direct readable fetch

Try lightweight conversion services first:

  1. r.jina.ai

    https://r.jina.ai/http://example.com
    
  2. markdown.new

    https://markdown.new/https://example.com
    
  3. defuddle

    https://defuddle.md/https://example.com
    

For deterministic retries, use the bundled script:

python {baseDir}/scripts/fetch_url.py "https://example.com/article"

The script returns JSON with:

  • chosen method
  • attempt history
  • blocked/thin-content detection
  • final content when successful

Use these when the user wants article text, page summaries, or structured extraction from normal public pages.

2) Detect failure modes early

Treat the fetch as failed or unreliable if you see signs like:

  • Just a moment...
  • Performing security verification
  • Enable JavaScript and cookies
  • CAPTCHA / challenge pages
  • login wall instead of target content
  • obvious truncation / missing article body

When this happens, stop treating the result as the page content.

3) Browser fallback for protected sites

For sites blocked behind Cloudflare or requiring real browser execution:

  • Prefer a real browser session via OpenClaw browser tools when available.
  • If the user is using the Chrome relay/extension, ask them to attach the tab and then inspect the live rendered page.
  • Snapshot the page and extract only the needed fields.

Use browser fallback for:

  • JS-heavy pages
  • Cloudflare-protected pages
  • sites that render key content after load
  • pages where the direct markdown services return verification screens

4) Search / indexed fallback

If direct fetch and browser fetch are not available or still fail:

  • search for the exact page / journal / article title
  • use search snippets, publisher mirror pages, cached summaries, or secondary sources
  • prefer official publisher pages when search can surface the needed field
  • clearly label data as secondary-source derived if it was not read directly from the target page

This is often enough for metadata tasks like:

  • editor-in-chief names
  • journal impact factors
  • publication frequency
  • ISSN
  • institutional affiliations

5) Partial-completion mode

If a site is inconsistent, return a mixed result instead of stalling:

  • fill the rows that can be verified directly
  • mark blocked / unresolved rows clearly
  • explain what failed and which fallback was used

Practical extraction strategy

For one page

  1. Try r.jina.ai
  2. If blocked, try markdown.new
  3. If blocked, try defuddle
  4. If still blocked, use browser tools
  5. If browser unavailable, use search/indexed fallback
  6. Report confidence level

For many similar pages

  1. Fetch the index/list page first
  2. Extract all target URLs or codes
  3. Process pages in batches
  4. Record success/failure per row
  5. Retry only failures with stronger fallback methods
  6. Deliver the best complete table possible

Output guidance

When extracting structured data, prefer columns like:

  • source URL
  • extraction method (direct, browser, search, secondary)
  • confidence (high, medium, low)
  • note for blocked/unverified rows

Examples

  • User: "Read this article" → direct fetch first
  • User: "What does this page say?" → direct fetch, then browser fallback if blocked
  • User: "Crawl this journal site" → index page first, then batched extraction with fallback chain
  • User: "Cloudflare blocked it" → switch to browser or search fallback, do not keep retrying the same failed method
安全使用建议
This skill will forward the requested page URL to third‑party URL-to-Markdown services (r.jina.ai, markdown.new, defuddle.md) as its primary retrieval method. Before installing or using: (1) avoid fetching pages that contain private, confidential, or sensitive information because that content may be proxied and possibly stored by those external services; (2) consider telling users and obtaining consent before fetching private pages; (3) if privacy is important, prefer a browser-based/local headless fetch or a self-hosted reader instead of public proxy services; (4) be aware the simple classifier in the bundled script uses heuristics (marker phrases and length) and can misclassify pages as blocked or 'thin'; (5) if you need stronger guarantees about where data goes, request the skill owner to add explicit warnings and an option to disable third-party proxies or to use self-hosted alternatives. If you want a stricter assessment, provide the deployment environment (where the agent runs) and whether you expect to fetch authenticated/private pages — that would change the risk evaluation.
功能分析
Type: OpenClaw Skill Name: aurthes-web-fetcher Version: 1.2.0 The skill is a standard web-content extractor designed to fetch and convert web pages into readable markdown using third-party services (r.jina.ai, markdown.new, and defuddle.md). The Python script (scripts/fetch_url.py) implements a clean fallback logic using standard libraries and includes basic detection for bot-protection screens (e.g., Cloudflare). There is no evidence of data exfiltration, malicious execution, or prompt injection.
能力评估
Purpose & Capability
Name, description, SKILL.md and the bundled script all align: the skill fetches and extracts readable web content and implements a clear fallback chain. Using external URL-to-Markdown services is consistent with the 'low-friction' design, but it is a design choice that has privacy implications (see instruction_scope).
Instruction Scope
The runtime instructions and bundled script explicitly send the target URL to third-party conversion services (r.jina.ai, markdown.new, defuddle.md) and return the fetched content. That means the full target page (including any sensitive data present on it) may be proxied through those external services. SKILL.md does not require or document user consent, nor does it warn about possible storage/retention or confidentiality implications. Aside from this, the instructions stay within the stated purpose and do not ask to read unrelated files or environment variables.
Install Mechanism
Instruction-only skill with one small bundled Python script. There is no install spec, no downloads from external URLs, and nothing is written to disk beyond the included file. This is low installer risk.
Credentials
The skill requests no environment variables, credentials, or config paths. It does not require any unrelated secrets or permissions.
Persistence & Privilege
always is false and the skill is user-invocable. It does not request permanent presence or system-wide changes. The skill can be invoked autonomously by the agent (default behavior) but that is normal and not by itself a red flag.
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 aurthes-web-fetcher
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /aurthes-web-fetcher 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
v1.2.0
Add script-based fallback fetcher and improved Cloudflare/challenge handling guidance
v1.0.0
Initial release of web-fetcher skill: - Fetches web pages and converts them to Markdown for easier reading and processing. - Automatically tries multiple conversion services (r.jina.ai, markdown.new, defuddle.md) for the best chance of success. - Designed for tasks involving reading, extracting, or crawling content from specific URLs. - Example usage instructions and fallback strategy included in skill documentation.
元数据
Slug aurthes-web-fetcher
版本 1.2.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

Web Fetcher 是什么?

Fetch web pages and extract readable content for AI use. Use when reading, summarizing, or crawling a specific URL or small set of URLs. Prefer low-friction... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 341 次。

如何安装 Web Fetcher?

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

Web Fetcher 是免费的吗?

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

Web Fetcher 支持哪些平台?

Web Fetcher 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 Web Fetcher?

由 Aurthes(@aurthes)开发并维护,当前版本 v1.2.0。

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