Skip to main content
Glama
niyogi

chatgpt-ads-manager-mcp

by niyogi

update_ad_group

Update ad group details by ID, including name, status, bidding, and targeting, to refine campaign performance.

Instructions

Update an ad group by ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
statusNo
ad_group_idYesAd group ID.
descriptionNo
product_setNo
ad_account_idNo
context_hintsNo
bidding_configNo
landing_page_configurationNo
Behavior2/5

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 only states that an update occurs and does not explain whether the update is partial or full, what fields can be modified, whether status changes have side effects, or what response to expect. This is minimal transparency for a mutation tool.

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 a single, focused sentence with no wasted words. It is front-loaded and easy to parse, though its brevity contributes to the lack of semantic depth in other dimensions.

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

Completeness1/5

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

For a tool with 9 parameters, nested objects, an enum, no output schema, and no annotations, this description is far too incomplete. It does not explain which fields may be updated, how status interacts with dedicated status tools, or what configuration objects like bidding_config and landing_page_configuration contain, leaving agents without enough context to use the tool reliably.

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 only 11%, with 8 of 9 parameters undocumented. The description adds no meaning for name, status, description, product_set, ad_account_id, context_hints, bidding_config, or landing_page_configuration. The only hint, 'by ID,' merely reinforces the required ad_group_id field already present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the operation as updating an ad group, identified by ID. It distinguishes the tool from list/get/create operations but does not differentiate it from sibling tools like pause_ad_group, activate_ad_group, or archive_ad_group, which are also ad group modifications.

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

Usage Guidelines2/5

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

No usage guidance is provided. The description does not explain when to use update_ad_group versus pause_ad_group, activate_ad_group, archive_ad_group, or even update_campaign. An agent is left to infer the appropriate context from the tool name and parameter schema alone.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/niyogi/chatgpt-ads-manager-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server