seo-console-mcp

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ads_update_batch

Change multiple Google Ads keyword bids or campaign budgets in one call, with dry-run validation and safeguards that refuse unmatched entries or excessive total spend.

Instructions

Change several Google Ads keyword bids, or several campaign daily budgets, in one call. It is a named list of pairs, not a rule applied to many things: each entry names one target and the value it should end at, and an entry that matches no row or more than one refuses the whole batch before anything is written. The sum is guarded as well as each entry, because separately reasonable raises are one large spend change together. Dry run unless dryRun is false, and every value is read back afterwards

Input Schema

TableJSON Schema

Name	Required	Description
`kind`	Yes	One kind per call. A summed guard is only honest inside one kind: bids and budgets sum to dollars, statuses do not, and mixing them makes the total unreadable
`dryRun`	No	Resolve and price every entry and report the total, without changing anything
`changes`	Yes	A named list of pairs, each with its own value. There is no selector form: enumeration cannot make the mistake that a pattern can
`confirm`	No	Perform the batch even though a guard tripped. The dry run lists every reason, so this confirms something already read

Output Schema

TableJSON Schema

Name	Required	Description
`kind`	Yes
`notes`	Yes
`applied`	Yes
`entries`	Yes
`customerId`	Yes
`totalAfter`	Yes
`totalBefore`	Yes	Null when any entry has no current value to read, because a total that counts unknowns as zero is not a total
`totalGuards`	Yes	Guards on the batch as a whole. Five individually reasonable raises are one large spend change, and doing them one at a time is how that gets missed
`totalSummary`	Yes	The batch total in words, always present whether or not anything tripped. The sentence is what gets read; the guard is only what stops you when it is not

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.18.0Sep 24, 2026

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers: it discloses dry-run behavior, atomic refusal when an entry matches zero or many rows, per-entry and summed spend guards, and read-back verification after writing. These are critical behavioral details that go well beyond what the schema alone reveals.

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?

The description is compact, front-loaded with the main purpose, and each sentence adds a distinct behavioral guarantee. Nothing is redundant or filler; the length is appropriate for the tool's complexity.

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?

For a guarded batch mutation tool with a complex failure model, the description covers the essential invocation constraints, safety behavior, and post-write verification. The output schema handles return-value documentation, so the description is sufficiently complete for an agent to call the tool correctly.

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?

The input schema already has rich descriptions for all four parameters, so the baseline is 3. The description reinforces key meanings, such as the kind restriction and the named-pair form of changes, but it does not add substantial semantic detail beyond the schema's own parameter documentation.

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?

The description starts with a specific verb and resource: changing several Google Ads keyword bids or campaign daily budgets in one call. It clearly distinguishes this batch tool from a rule-based or singular update, making the tool's scope immediately recognizable relative to siblings like ads_update.

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?

It clearly implies when to use the tool: when updating multiple named targets in one call. It describes the intended shape as an explicit list of pairs rather than a broad rule, which guides appropriate invocation. It does not explicitly name alternative sibling tools, but the context is sufficient for an agent to decide when this batch operation is appropriate.

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