Ottom

Check how ready a store is for AI agents

check_store_readiness

Read-onlyIdempotent

Runs a light check of one store page, the way an AI shopping agent reads it: robots.txt, llms.txt, the product feed, the UCP manifest, structured data (product, price, availability, GTIN) and whether the price is in text an agent can read. Each finding comes with a plain explanation, a fix and a link to read more. If the store’s owner publishes an Ottom result with the Ottom badge, that result is included too. Pass a product page URL for the most findings; a home page works. Every answer links to a full scan on ottom.io.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "url": "<url>"
    },
    "name": "check_store_readiness"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes	A store page, ideally a product page, e.g. yourstore.com/products/your-product

Output Schema

Name	Required	Description
`url`	Yes	The page that was checked, as Ottom read the address.
`host`	Yes	The store’s host name.
`fullScan`	Yes	A full scan, in which an AI agent tries to buy.
`lightCheck`	Yes	A light check of the page, run now or in the last 30 minutes.
`publishedResult`	Yes	The store’s own Ottom result, only when its owner publishes it with the Ottom badge. Null for every other store.
`publishedResultNote`	Yes	One sentence saying where the result comes from.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 13, 2026

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=true), and the description adds real context beyond them: what is inspected, that each finding carries an explanation, a fix and a read-more link, that a published Ottom result with badge is merged in, and that every answer links to a full scan. It does not mention rate limits, caching, or behavior on unreachable pages, keeping it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and scope, then what is checked, then what the output contains, then input advice. Sentences earn their place, though the closing 'Every answer links to a full scan on ottom.io' leans promotional and could be folded into the output description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and annotations declaring the safety and openness profile, the description covers what an agent still needs: the scope of the check, the input expectation, and that results include explanations, fixes and links. Nothing required to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the single url parameter is already documented with an example, so the baseline would be 3. The description adds meaning beyond the schema by stating that a product page yields the most findings while a home page is acceptable, which guides URL choice rather than merely restating the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (runs a light check) plus the exact resource (one store page) and enumerates what it inspects: robots.txt, llms.txt, product feed, UCP manifest, structured data, and text-readable price. The phrase 'a light check' plus the closing pointer to 'a full scan on ottom.io' implicitly separates it from heavier alternatives like get_benchmark and list_checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Offers input-selection guidance ('Pass a product page URL for the most findings; a home page works'), which is genuinely useful. However, it never says when to choose this tool over get_benchmark or list_checks, and gives no exclusions or preconditions, so the when-to-use decision is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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