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Markdown Browser

Wrapper skill for OpenClaw web_fetch results. Use when you need MECE post-processing on fetched pages: policy decision from Content-Signal, privacy redaction...

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版本1.0.0
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技能说明


name: markdown-browser description: "Wrapper skill for OpenClaw web_fetch results. Use when you need MECE post-processing on fetched pages: policy decision from Content-Signal, privacy redaction, optional markdown normalization fallback, and stable output schema without re-implementing network fetch."

Markdown Browser Skills

This skill is an orchestration layer, not a replacement fetcher. It always keeps official web_fetch as the fetch source of truth.

MECE Architecture

  1. Fetch layer (official, exclusive)
  • Use OpenClaw web_fetch to retrieve the page.
  • Do not call direct HTTP fetch inside this skill for normal operation.
  1. Policy layer (these skills)
  • Parse Content-Signal and compute policy_action.
  • Current action focuses on ai-input semantics: allow_input, block_input, needs_review.
  1. Privacy layer (these skills)
  • Redact path/fragment/query values in output URL fields.
  • Keep URL shape useful for debugging without leaking sensitive values.
  1. Normalization layer (these skills)
  • If contentType=text/markdown, keep content as-is.
  • If contentType=text/html, convert with turndown as fallback enhancement.
  • For other content types, pass through text.

Execution Order

  1. Call official web_fetch.
  2. Pass the result JSON into this wrapper.
  3. Optionally pass Content-Signal and x-markdown-tokens header values if available.
  4. Use the returned normalized object for downstream agent logic.

Wrapper Tool

process_web_fetch_result({ web_fetch_result, content_signal_header, markdown_tokens_header })

Input:

  • web_fetch_result (required): JSON payload returned by OpenClaw web_fetch.
  • content_signal_header (optional): raw Content-Signal header string.
  • markdown_tokens_header (optional): raw x-markdown-tokens header value.

Output:

  • content
  • format (markdown | html-fallback | text)
  • token_estimate (number | null)
  • content_signal
  • policy_action
  • source_url (redacted)
  • status_code
  • fallback_used

CLI Usage

# Install runtime dependency once inside the skill directory
npm install --omit=dev

# 1) Obtain a web_fetch payload first (from OpenClaw runtime)
# 2) Save it as /tmp/web_fetch.json
# 3) Run wrapper post-processing
node browser.js \
  --input /tmp/web_fetch.json \
  --content-signal "ai-input=yes, search=yes, ai-train=no" \
  --markdown-tokens "1820"

如何使用「Markdown Browser」?

  1. 打开小龙虾AI(Web 或 iOS App)
  2. 点击上方「立即使用」按钮,或在对话框中输入任务描述
  3. 小龙虾AI 会自动匹配并调用「Markdown Browser」技能完成任务
  4. 结果即时呈现,支持继续对话优化

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