xfix

Look up AI Shopping Readiness Index score

lookup_index_score

Read-only

Looks up a store domain in the xfix AI Shopping Readiness Index and returns its published score and the fields shown on the public Index page, or says the store is not in the Index. Does not fetch the store.

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": {
      "domain": "<domain>"
    },
    "name": "lookup_index_score"
  }
}

Input Schema

Name	Required	Description	Default
`domain`	Yes	The store's domain, for example yourstore.com.

Output Schema

Name	Required	Description	Default
`url`	Yes
`tool`	Yes
`index`	No
`cached`	Yes
`limits`	Yes
`status`	Yes
`verdict`	Yes
`findings`	Yes
`checked_at`	Yes
`report_url`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 19, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, destructiveHint=false, openWorldHint=false), and the description adds meaningful behavior beyond them: the not-in-Index outcome, the fact that the response mirrors the public Index page fields, and the explicit "does not fetch the store" scope boundary. It doesn't mention rate limits or caching, but it exceeds the annotation baseline.

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

Conciseness5/5

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

Two tight sentences with no filler; the core action and its scope boundary ("Does not fetch the store") are front-loaded before the failure case. Every clause carries information.

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

Completeness4/5

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

For a one-parameter read tool with full annotation coverage and an output schema, the description is essentially complete: it covers the lookup, the return shape at a high level, the negative outcome, and the scope limit. It could still say explicitly when this beats check_store_ai_readiness, but nothing needed 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.

Parameters3/5

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

With a single parameter at 100% schema description coverage, the schema already defines "domain" with a format example. The description restates that the input is a store domain but adds no extra syntax, normalization, or edge-case guidance, so the baseline 3 applies.

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

Purpose4/5

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

The description names a specific verb and resource ("Looks up a store domain in the xfix AI Shopping Readiness Index") and states what is returned (published score plus the public Index page fields). It implicitly differentiates itself from the check_* siblings with "Does not fetch the store," though it never names them explicitly, so sibling differentiation is inferential rather than stated.

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?

"Does not fetch the store" implies this is for retrieving an already-published score rather than running a live analysis, which gestures at when to prefer it over check_store_ai_readiness. However, there is no explicit when-to-use/when-not statement or named alternative, so the agent must infer the routing rule.

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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