google_ads_asset_requirements_get
Return asset requirements for a Google Ads channel type.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| customer_id | Yes | 10-digit Google Ads customer id. | |
| channel_type | Yes | ||
| connection_context | No |
Return asset requirements for a Google Ads channel type.
| Name | Required | Description | Default |
|---|---|---|---|
| customer_id | Yes | 10-digit Google Ads customer id. | |
| channel_type | Yes | ||
| connection_context | No |
Changes observed during successful MCP inspections.
Input schema / properties / connection_contextAdded value: +{
+ "pattern": "^mctx_v1_[0-9a-f]{64}$",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=false, destructiveHint=false, so the safe-read profile is covered. The description adds that results are scoped by channel type, but says nothing about output shape or whether requirements vary by customer, which would matter for a lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short, front-loaded sentence with no waste. Appropriately sized, though it is perhaps too terse given the gaps in parameter semantics.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
A three-parameter lookup with no output schema and poor schema coverage needs more than one sentence. The absent enum for channel_type and the unexplained connection_context parameter are material omissions for an agent trying to call this correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 33%: customer_id is documented, but channel_type has no description and no enum, and connection_context is unexplained. The description does not compensate by listing valid channel types or explaining the connection_context requirement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: returns asset requirements for a channel type. Clear what it does, but doesn't differentiate from nearby creation-prep tools like google_ads_creation_capabilities_get or asset_upload_prepare which also touch asset requirements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this versus alternates such as google_ads_creation_capabilities_get, google_ads_field_metadata, or the asset_upload_prepare flow. The agent must infer that this is a lookup step before asset creation.
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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