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niyogi

chatgpt-ads-manager-mcp

by niyogi

list_conversion_event_settings

Retrieve conversion event settings for an ad account to identify IDs needed for campaign conversion tracking and bidding setup.

Instructions

List conversion event settings for the ad account. Use IDs with campaign conversion_event_setting_ids and conversions bidding.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
afterNo
limitNo
orderNo
beforeNo
ad_account_idNo
Behavior2/5

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

There are no annotations, so the description carries the full behavioral burden. It conveys that this is a read-only list operation, but it does not disclose pagination behavior, ordering/defaults, scoping semantics, or what the returned settings represent beyond the name. This leaves meaningful behavioral gaps.

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?

The description is short and front-loaded, with the primary purpose stated in the first sentence. The second sentence adds usable downstream context, though it is a bit cryptic; overall it avoids waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With five parameters, 0% schema coverage, no annotations, and no output schema, the description is not complete enough. It provides the core purpose and a use case, but leaves pagination parameters, return shape, and potential filtering semantics unexplained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for the five undocumented parameters. It only echoes the 'ad account' concept and vaguely refers to output IDs, but says nothing about `after`, `before`, `limit`, or `order`. No added semantic meaning beyond the bare schema property names is provided.

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 clearly states the action ('List'), the resource ('conversion event settings'), and the scope ('for the ad account'). This is specific enough to distinguish it from siblings like 'list_conversion_events' and 'create_conversion_event_setting'.

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

Usage Guidelines3/5

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

The description gives a practical downstream context: the returned IDs should be used with 'campaign conversion_event_setting_ids' and 'conversions bidding'. However, it does not explicitly explain when to choose this tool over sibling tools such as 'list_conversion_events', so the when-to-use guidance is only implied.

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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