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Web Fetcher

作者 Aurthes · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install aurthes-web-fetcher-v2
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 appears to only fetch and return page text; it does not ask for credentials or install software. However, note two practical privacy points before installing: (1) The preferred fetch methods send the target URL (and the fetched page content as processed) to third-party conversion services (r.jina.ai, markdown.new, defuddle). If the page is sensitive or behind a private network, do not use those services — prefer a browser attach or local fetch. (2) The SKILL.md recommends attaching browser tabs or using a Chrome relay/extension for protected pages; attaching a live tab can expose page content (and potentially authenticated sessions) to the agent. Only attach tabs you trust and are comfortable sharing. If you need more assurance, ask the maintainer for a privacy policy or run the included script locally to inspect behavior yourself.
功能分析
Type: OpenClaw Skill Name: aurthes-web-fetcher-v2 Version: 1.1.0 The skill bundle is a well-structured tool for fetching and converting web pages into AI-readable markdown using a multi-layered fallback strategy. The Python script (scripts/fetch_url.py) uses standard libraries to interface with legitimate third-party conversion services (r.jina.ai, markdown.new, defuddle.md) and includes logic to detect bot-protection screens. No evidence of data exfiltration, malicious execution, or prompt injection was found.
能力评估
Purpose & Capability
Name and description match what is implemented: lightweight remote conversion services + browser fallback. The included Python script and SKILL.md only perform HTTP fetches and classification; no unrelated credentials, binaries, or system access are requested.
Instruction Scope
Instructions stay within the purpose (try conversion services, then browser or search fallback). They advise using OpenClaw browser tools or a Chrome relay/extension and to ask users to attach tabs when necessary — this is expected for accessing authenticated or JS-heavy pages, but it implies the user may share a live tab with the agent, so the user should be aware of what context they attach.
Install Mechanism
No install spec — instruction-only with a small included Python script. Nothing is downloaded from third-party URLs during install, so there is no on-install code-fetch risk.
Credentials
Skill requests no environment variables, credentials, or config paths. The behavior (fetching public URLs and recommending browser attach for protected pages) is proportionate to the stated purpose.
Persistence & Privilege
always is false and the skill does not request persistent system-wide privileges or modify other skill configs. Autonomous invocation is allowed by default and is not in itself a concern here.
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-v2
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /aurthes-web-fetcher-v2 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
v1.1.0
- Improved reliability by introducing a fallback chain: prefer fast markdown services first, then use browser tools or search/indexed sources if direct fetch fails. - Added stricter rules for detecting Cloudflare blocks, login walls, and incomplete content; instructs not to treat failed fetches as valid. - Provided step-by-step extraction strategies for both single and multi-page tasks, with guidance for handling partial completions and blocked cases. - Clarified preferred output structure, including extraction method, confidence scores, and notes for any blocked or unresolved data. - Updated examples to illustrate the new workflow and fallback logic for common scenarios.
元数据
Slug aurthes-web-fetcher-v2
版本 1.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
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 263 次。

如何安装 Web Fetcher?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install aurthes-web-fetcher-v2」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 v1.1.0。

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