# Start Here: The 30-Minute Agent Selection Triage

> Start with the readiness checklist if you have not shipped an agentic protocol yet, or the selection checklist if you have and agents still are not choosing you.

<!-- New here? A 30-minute triage: which checklist to run first, and the shortest reading path through AgentMint.net for your situation. -->
<!-- Canonical: https://agentmint.net/start/ · By Abdalsalaam Halawa · Published 2026-07-08 -->
<!-- Evidence tags below are load-bearing: <Claim type="spec-fact|reported|hypothesis"> marks how each factual claim is sourced. -->

<KeyTakeaways
  items={[
    "Agent selection is not SEO: agents score structured product data, not brand recall, so the fix looks different from ranking a page.",
    "Two checklists answer two different questions. Readiness asks whether an agent can find and transact with your store at all. Selection asks whether you win once you are eligible.",
    "Have not shipped a protocol yet? Start with the readiness checklist. Shipped one and still not chosen? Skip straight to the selection checklist.",
    "Three reading paths below take you through 4 to 5 pages, in order, for your specific situation, in under 30 minutes.",
    "The glossary and research lab are there for depth once you know what to look up next.",
  ]}
/>

## What "agent selection" means here (and why it is not SEO)

An AI shopping agent, whether it is ChatGPT, Google's AI Mode and Gemini, Perplexity, Copilot, or Claude, does not scan a results page the way a person does. It reads your product data and returns one pick or a short list, and the choice it makes is what this site calls [agent selection](/glossary/#agent-selection). That is a different job from ranking a page for a human to click, and the full argument for why lives in [How AI Shopping Agents Choose Products](/how-ai-agents-choose-products/) and the flagship [Agentic Commerce Optimization](/agentic-commerce-optimization/) guide. This page skips that argument and gets you to the right next page for where you actually are.

## Which checklist do you need first?

Two checklists on this site answer two different questions, and starting with the wrong one wastes the 30 minutes you have.

- **You have not implemented ACP, UCP, or any agentic protocol yet.** Start with the [Agentic Shopping Readiness Checklist](/tools/agentic-readiness-checklist/). It checks whether an agent can find, parse, and transact with your store at all: the eligibility layer.
- **You have shipped a protocol and agents still are not choosing you.** Go straight to the [Agent Selection Checklist](/tools/agent-selection-checklist/). Eligibility is not your problem, so this checks the signals that decide who actually wins.
- **You are not sure which bucket you are in.** Read [How AI Shopping Agents Choose Products](/how-ai-agents-choose-products/) first. It draws the eligibility-versus-selection line in about five minutes, and you will know which checklist to run by the end.

## Three reading paths for your first 30 minutes

Pick the path that matches your situation. Each one is 4 to 5 pages, in the order we would read them.

### I have not touched any agentic protocol yet

1. [Agentic Commerce Optimization: The Complete Guide](/agentic-commerce-optimization/), for the full landscape before you touch anything.
2. [How AI Shopping Agents Choose Products](/how-ai-agents-choose-products/), for what an agent actually scores once it can see you.
3. [AI Crawlers, robots.txt & llms.txt for Stores](/ai-crawlers-robots-llms-txt/), to confirm agents can reach your pages at all.
4. [Agentic Shopping Readiness Checklist](/tools/agentic-readiness-checklist/), the self-audit for where you stand today.
5. [UCP vs ACP: Which Gets You Selected](/ucp-vs-acp/), once you pass the readiness checklist, for which protocol to ship next.

### I have shipped ACP or UCP but agents still are not picking me

1. [How AI Shopping Agents Choose Products](/how-ai-agents-choose-products/), for why shipping a protocol gets you eligible, not chosen.
2. The three content levers that measurably moved selection in the strongest evidence available: [Make Your Product Feed AI-Readable](/make-product-feed-ai-readable/), [Product Schema (JSON-LD) for AI Shopping](/product-schema-for-ai-shopping/), and [Product Titles That AI Agents Match](/product-titles-for-ai-agents/).
3. [AI Shopping Platforms: How to Get Selected Across Engines](/platforms/), to see where ChatGPT, Gemini, and Perplexity actually diverge before you optimize further.
4. [Agent Selection Checklist](/tools/agent-selection-checklist/), the flagship self-audit for the signals no validator checks.
5. [Why You're Not in ChatGPT Shopping](/store-not-in-chatgpt-shopping/), if ChatGPT specifically is the gap.

### I just want to understand the landscape first

1. [Agentic Commerce Optimization: The Complete Guide](/agentic-commerce-optimization/), the flagship pillar, start to finish.
2. [UCP vs ACP: Which Gets You Selected](/ucp-vs-acp/), the protocol landscape: what each open standard actually governs.
3. [Agentic Payment Protocols, Explained](/agentic-payment-protocols/), the payment rails sitting under the protocols.
4. [AI Shopping Platforms: How to Get Selected Across Engines](/platforms/), engine by engine, where ChatGPT, Gemini, and Perplexity currently diverge.
5. [Agentic Commerce Glossary](/glossary/), the terms, defined and sourced, as you go.

## Where to go deeper later

Once you have run a checklist and read your path, two places hold the rest of the site.

- **[Agentic Commerce Glossary](/glossary/)**: every term on this site defined once, sourced, and evidence-typed, including [agent selection](/glossary/#agent-selection) and [agent win rate](/glossary/agent-win-rate/), the metric we propose for tracking whether the work above is paying off.
- **[The AgentMint.net Research Lab](/research/)**: where we test claims about agent behavior on real catalogs rather than repeating vendor claims, methodology published before any results land.

<Callout variant="note" title="Agent behavior moves">
  Every page on this site types and dates its claims about how agents behave, because a model update can change what an agent rewards. Treat the reading paths above as a map of where to look, not a fixed formula, and expect to check back after a major model release.
</Callout>

You do not need the whole site today. Run the right checklist, follow one path, and come back for the rest when you need it.