Web extraction tools, especially those incorporating LLMs, risk generating fabricated data when faced with inaccessible or unreadable web pages. This can lead to poisoned data pipelines and flawed agent reasoning. A robust solution involves implementing strict checks to verify actual page content before LLM extraction, and returning structured, machine-readable errors when content is missing or unverifiable. This approach ensures that downstream processes, including AI agents, receive accurate information or clear failure signals, preventing the propagation of AI
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RANK_REASON [lever_c_demoted from research: ic=1 ai=1.0]