Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Research Agents

• URL: http://arxiv.org/abs/2608.02751v2
• Date: Wed, 05 Aug 2026 02:06:16 GMT
• Title: Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Research Agents
• Abstract summary: Existing deep-research agents use a Search--Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata.<n>We introduce textscSieve, a search--inspect-fetch strategy driven by a Boolean Query Language (BQL)<n>It searches webpage fields to filter candidates, uses an interchangeable ranker to order them, presents structure-rich result cards for inspection, and fetches only selected sections.
• Score: 50.35041517085015
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Existing deep-research agents use a Search--Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata. This prevents agents from directly constraining retrieval to parts of a webpage and often carries irrelevant content into their context. We introduce \textsc{Sieve}, a search--inspect--fetch strategy driven by a Boolean Query Language (BQL): it searches webpage fields to filter candidates, uses an interchangeable ranker to order them, presents structure-rich result cards for inspection, and fetches only selected sections. Across three QA collections, \textsc{Sieve} is more accurate than the strongest conventional Search--Visit configuration on each collection while using $20.7$--$50.6\%$ fewer tokens. Boolean filtering improves every tested ranker, and the accuracy--context advantage persists across retriever choices and agent backbones. Our implementation is included in the SkimSearchAgent library at https://github.com/ielab/skim-search-agent.

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