An Interactive Agent for Requirement-Driven Candidate Sourcing

• URL: http://arxiv.org/abs/2608.23501v1
• Date: Mon, 24 Aug 2026 17:04:16 GMT
• Title: An Interactive Agent for Requirement-Driven Candidate Sourcing
• Abstract summary: We present sys, the first requirements-driven candidate-sourcing agent.<n>It elicits, validates, retrieves, and verifies a vague people-request into a justified slate.<n>It dominates breadth ($100%$ coverage at $2.5times$ the yield) and is emphnear-orthogonal to the field.
• Score: 75.63902836826038
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Finding people from a natural-language description (``ML engineers transitioning to research roles in biotech'') is increasingly delegated to LLM agents and framed as information retrieval. We argue that it is fundamentally a requirements engineering task: such a request is an under-determined requirement with implicit constraints, many valid answers, and no acceptance criterion, so useful answers require eliciting, validating, and verifying the requirement before search can matter. We present \sys{}, to our knowledge the first interactive, requirements-driven candidate-sourcing agent (it elicits, validates, retrieves, and verifies a vague people-request into a justified slate through bounded elicitation, workflow templates, a two-stage commit protocol, and bidirectional termination guards) and \bench{}, a benchmark that runs the requirements lifecycle (criteria-anchored validation, multi-model evidence-grounded oracle construction, and cost-aware verification). Across $21$ systems and all $691$ requirements, \sys{} dominates breadth ($100%$ coverage at $2.5\times$ the yield) and is \emph{near-orthogonal} to the field, with $90%$ of the people it returns are surfaced by \emph{none} of $20$ strong LLM-plus-web baselines combined. Beyond breadth, an evidence-grounded judging of every system shows \sys{} \emph{recalls} the most relevant real people: $0.241$ of the union pool, $1.9\times$ the next system, with a bootstrap $95%$ interval disjoint from every baseline. \sys{} is thus the strongest \emph{sourcing} engine (the deepest real, reachable candidate pool), while precision-ranking LLMs serve as~complementary verifiers.

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