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google_ads_change_history_list

List recent change events on a Google Ads account for audit-trail diagnosis. Each event includes change date, resource type, operation, changed fields, and user email.

Instructions

List the most recent change_event rows on a Google Ads account, sorted newest-first and capped at 100. Returns [{change_date_time (Google-formatted timestamp string returned verbatim from the API — typically 'YYYY-MM-DD HH:MM:SS.ffffff+00:00' but no format coercion is applied, so callers should parse defensively), change_resource_type (enum string e.g. 'CAMPAIGN', 'CAMPAIGN_BUDGET', 'AD_GROUP', 'AD', 'CAMPAIGN_BID_MODIFIER'), resource_change_operation ('CREATE'|'UPDATE'|'REMOVE' as enum string), changed_fields (list of dotted field paths), user_email}]. Read-only. Defaults to the last 14 days when dates are omitted; the API rejects an open-ended range so mureo always fills one. Use this for audit-trail diagnosis. For narrower bid/budget-only filtering use google_ads_cost_increase_investigate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNoInclusive end date ('YYYY-MM-DD'). Default: today.
start_dateNoInclusive start date ('YYYY-MM-DD'). Default: today - 14 days.
customer_idNoGoogle Ads customer ID as a 10-digit string without dashes (e.g. '1234567890'). Optional — falls back to GOOGLE_ADS_CUSTOMER_ID / GOOGLE_ADS_LOGIN_CUSTOMER_ID from the configured credentials when omitted.
Behavior4/5

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

No annotations provided, but description states read-only nature, return format with field descriptions, and default behavior for missing dates. Could mention pagination or rate limits, but sufficient for this context.

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?

Front-loaded with main purpose, then return format, then usage guidance. No redundant sentences; every sentence adds value.

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?

No output schema, but description provides full return format with field types and examples. Also covers date range behavior and sibling differentiation, making it self-contained.

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 description adds value by reiterating defaults and explaining why the date range is always filled (API rejects open-ended). This goes beyond schema details.

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?

Description clearly states it lists change_event rows, newest-first, capped at 100. It specifies the resource (Google Ads account) and provides differentiation from sibling tool google_ads_cost_increase_investigate for narrower filtering.

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

Usage Guidelines5/5

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

Explicit guidance: 'Use this for audit-trail diagnosis' and provides alternative for bid/budget-only filtering. Also discloses default date range and API constraint on open-ended ranges.

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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