Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Wrapper skill for OpenClaw web_fetch results. Use when you need MECE post-processing on fetched pages: policy decision from Content-Signal, privacy redaction...
Wrapper skill for OpenClaw web_fetch results. Use when you need MECE post-processing on fetched pages: policy decision from Content-Signal, privacy redaction...
This item's current download entry is known to bounce back to a listing or homepage instead of returning a package file.
Use the source page and any available docs to guide the install because the item currently does not return a direct package file.
I tried to install a skill package from Yavira, but the item currently does not return a direct package file. Inspect the source page and any extracted docs, then tell me what you can confirm and any manual steps still required. Then review README.md for any prerequisites, environment setup, or post-install checks.
I tried to upgrade a skill package from Yavira, but the item currently does not return a direct package file. Compare the source page and any extracted docs with my current installation, then summarize what changed and what manual follow-up I still need. Then review README.md for any prerequisites, environment setup, or post-install checks.
This skill is an orchestration layer, not a replacement fetcher. It always keeps official web_fetch as the fetch source of truth.
Fetch layer (official, exclusive) Use OpenClaw web_fetch to retrieve the page. Do not call direct HTTP fetch inside this skill for normal operation. Policy layer (these skills) Parse Content-Signal and compute policy_action. Current action focuses on ai-input semantics: allow_input, block_input, needs_review. Privacy layer (these skills) Redact path/fragment/query values in output URL fields. Keep URL shape useful for debugging without leaking sensitive values. 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.
Call official web_fetch. Pass the result JSON into this wrapper. Optionally pass Content-Signal and x-markdown-tokens header values if available. Use the returned normalized object for downstream agent logic.
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
# 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"
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