[ agent selection ]

Win the agent's choice.

AgentMint.net is a research publication and practitioner handbook on agent selection: why AI shopping agents pick one store, product, or offer over another, and how merchants win that choice.

[ how we source ]

Every factual claim is labeled by how it's sourced. You see the evidence, not just the assertion:

In a controlled simulation, moving a product from the bottom-right corner to the top row raised its selection rate roughly fivefold for a Claude Sonnet 4 agent.ReportedACES (arXiv:2508.02630) (2025)

[ start here ]

Choose your path

Learn the model

How AI shopping agents actually decide, and the evidence behind each signal.

Diagnose a problem

Not showing up, or showing up and losing? Find where it's failing.

By role: Store owner: the 30-minute triageDeveloper: the blueprints collectionSEO / feed lead: make your feed AI-readableAgency: the platform playbooks

New here? Start with the 30-minute triage, which routes you by situation and role.

[ evidence ]

How we source every claim

Every factual statement on AgentMint.net carries an evidence tag: spec-fact (in an official spec, linked), reported (a named, dated third-party source), or hypothesis (our own labeled inference). Nothing is asserted that we can't show. Read how we work →

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[ who reads AgentMint.net ]

Written for the people who ship the catalog.

Rigor over hype. If you distrust marketing claims and want to see the sourcing behind every one, this is for you.

  • Developers
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  • Growth teams
  • Agencies
  • Merchants

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