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Merchant Center issues by ad spend

merchant_ad_spend
Read-only

Find which Merchant Center product issues cost money by ranking disapproved, limited, or pending products by Shopping and Performance Max spend, conversions, and value, and flag stopped spend.

Instructions

Which Merchant Center problems cost money: products that are disapproved, limited or pending, joined with what they earned in Shopping and Performance Max ads (cost, clicks, conversions, conversion value) over the window, most value first, and whether each has stopped spending in the last 7 days. Use it when Shopping or Performance Max results drop, before fixing issues one by one. Changes nothing.

Input Schema

NameRequiredDescriptionDefault
daysNoLook-back window in days, ending yesterday; reach back before a drop
limitNoMost products to return
account_idYesMerchant Center account ID, digits only (from merchant_accounts)
customer_idYesGoogle Ads customer ID, with or without dashes (from list_accounts)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.25.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint, and the trailing 'Changes nothing' only restates that. The genuinely additive context is behavioral output detail — value-descending ordering and the last-7-days stopped-spending flag — but there is no discussion of rate limits, data freshness, or how missing spend data is represented.

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?

One dense but well-ordered sentence front-loads the core purpose, then usage guidance, then the safety note. Every clause adds something, though the packed parenthetical of metrics is slightly heavy.

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 no output schema, the description must describe returns, and it does: the issue states, the joined ad metrics, the sort order, and the stopped-spending flag. Combined with a fully covered input schema, an agent has everything needed to call and interpret it.

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?

Schema description coverage is 100%, so all four parameters are already documented in the schema, including the days window and limit. The description reinforces the window concept ('over the window', 'reach back before a drop') but adds no syntax, constraints, or semantics beyond the schema, so baseline 3 applies.

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 resource and outcome: disapproved/limited/pending products joined with Shopping and Performance Max ad spend. It explicitly names return fields (cost, clicks, conversions, conversion value) and ordering (most value first), which distinguishes it clearly from merchant_product_issues.

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

Usage Guidelines4/5

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

Gives a clear trigger: 'Use it when Shopping or Performance Max results drop, before fixing issues one by one.' That implies the alternative (merchant_product_issues without spend context) but never names it explicitly, so there is no explicit exclusion or named alternative.

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