[ 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.
Implement improvements
Copy-paste blueprints and executable guidance for your stack.
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 →
[ stay current ]
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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
- Technical SEO leads
- Growth teams
- Agencies
- Merchants