ResearchClaw

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Overview

OpenClaw-powered agent that finds and ranks researchers from papers, writes plain-English hiring theses, and drafts cold emails referencing their work.

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Best For Professions:

recruiters talent acquisition founders cto r&d leaders product managers

ResearchClaw is an OpenClaw-powered research hiring agent that helps teams identify academics whose published work matches a specific product or AI use case. You describe your use case in plain English, and the system decomposes it into structured queries, pulls papers and author metadata from sources like Semantic Scholar, arXiv, and OpenAlex, and ranks candidates using embedding similarity combined with citation- and recency-weighted scoring. It then generates an LLM-written hiring thesis for each researcher (translating academic jargon into product-relevant reasoning) and drafts hyper-personalized cold emails that reference specific papers and contributions, with options like CSV export and outreach automation.

Autonomy level

62%

Reasoning: It takes a single high-level input (your use case) and runs a multi-step pipeline: query decomposition, multi-source retrieval, ranking, summarization, and outreach drafting. It produces structured outputs (ranked researchers, theses, emails, CSV export) with limited further user steering. It does not clearly indicate it can autonomously execute lo...

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Some of the use cases of ResearchClaw:

Finding researchers whose published work directly aligns with your technical product challenge.
Ranking candidates using embedding similarity with citation- and recency-weighted scoring.
Converting dense academic work into plain-English hiring theses tied to your use case.
Drafting personalized outreach emails that reference specific papers and contributions.

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