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Python
Hybrid

google_ads_conversions_update

Partially update a Google Ads conversion action by changing only the specified fields—name, category, status, default value, or attribution windows—while preserving all other settings.

Instructions

Update fields on an existing Google Ads conversion action via FieldMask mutate. Returns {resource_name} of the updated row. Mutating — partial update: only the fields you pass are modified, the rest are preserved. At least one updatable field must be supplied (name, category, status, default_value, always_use_default_value, click_through_lookback_window_days, view_through_lookback_window_days) or the call raises ValueError. To delete/archive an action use status 'REMOVED' here or call google_ads_conversions_remove.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoNew display name (max 256 characters). Omit to leave the name unchanged.
reasonNoWhy this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.
statusNoNew status. 'ENABLED' counts toward 'Conversions' column; 'HIDDEN' excludes it from the column but keeps the action; 'REMOVED' archives it.
categoryNoNew category. Must match the allowed enum.
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.
default_valueNoNew default conversion value in account currency.
conversion_action_idYesConversion action ID as a numeric string (e.g. '987654321'). Obtain via google_ads_conversions_list.
always_use_default_valueNoToggle whether default_value always overrides tag-supplied values.
view_through_lookback_window_daysNoNew view-through attribution window in days (1-30).
click_through_lookback_window_daysNoNew click-through attribution window in days (1-90).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.20.0
    • addedInput schema / properties / reason
      Added value: +{
+  "description": "Why this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.",
+  "maxLength": 500,
+  "type": "string"
+}
  2. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  3. Addedv0.10.11
  4. Removedv0.10.9
  5. Addedv0.9.12
  6. Removedv0.9.6
  7. Addedv0.9.2
  8. Removedv0.9.1
  9. Addedv1.0.5

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explains that this is a partial update where unpassed fields are preserved, that calling without an updatable field raises ValueError, that REMOVED archives the action, and that the response contains the resource_name. This is substantive and goes well beyond the tool name.

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?

Three dense sentences, front-loaded with purpose and return value, then mutating semantics, then error behavior and deletion alternative. Every sentence earns its place; no filler or repetition.

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 mutation tool with no annotations and no output schema, the description covers purpose, return value, partial-update semantics, error conditions, and delete routing. Parameter details are fully handled by the schema, so nothing essential is missing for correct invocation.

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 description coverage is 100%, so the per-field semantics are already well documented. The description adds value by enumerating the updatable field set and the critical constraint that at least one must be supplied, which prevents an otherwise easy invocation mistake.

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, resource, and mechanism: 'Update fields on an existing Google Ads conversion action via FieldMask mutate.' It also clarifies the return value and distinguishes itself from create/remove operations by describing partial updates and the deletion alternative.

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?

Provides explicit guidance for deletion/archival ('use status REMOVED here or call google_ads_conversions_remove') and specifies the minimum invocation requirement that at least one updatable field must be supplied. It does not explicitly contrast with create for new conversion actions, but the update semantics make this clear enough.

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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