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niyogi

chatgpt-ads-manager-mcp

by niyogi

get_campaign_insights

Retrieve performance metrics for a single campaign by providing its campaign ID. Define fields, filters, segments, and time ranges to target the exact insights your analysis needs.

Instructions

Get campaign insights. Chain from list_campaigns -> campaign_id. Same params as ad account insights but scoped to one campaign.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort specs, e.g., ["-impressions"].
afterNoCursor for pagination.
limitNoMax rows 1–2000.
beforeNoCursor for pagination.
fieldsNoFields to return, e.g., ["impressions","clicks","spend_micros"].
filtersNoFilters array (opaque, enumerated in docs).
includesNo
segmentsNoSegments: product, country, device, etc. For product breakdown add product.feed_id + product.item_id to fields.
campaign_idYesCampaign ID.
time_rangesNoTime ranges, e.g., ["2026-01-01:2026-01-31"]. Check docs for format; required for conversion insights.
ad_account_idNo
time_granularityNoTime bucket. Use daily for trend analysis.
aggregation_levelNoAggregation scope.
override_segment_group_orderNo
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the tool is scoped to one campaign and that campaign_id should come from list_campaigns, but it does not describe the return shape, read-only nature explicitly, rate limits, authentication requirements, or any pagination/data-freshness behavior. The name implies a read operation, but the description itself adds little behavioral transparency.

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?

Two compact sentences with no filler. The core scope statement is front-loaded, and both sentences earn their place by explaining what the tool does and how to invoke it correctly.

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

Completeness3/5

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

Given the tool's complexity (14 parameters, no output schema, no annotations), the description is adequate but thin. It provides the essential chaining workflow and scope, but it leaves important contextual details—such as expected output format, required parameters for conversion insights beyond what the schema notes, and operational caveats—to be inferred or looked up elsewhere.

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

Parameters3/5

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

Schema description coverage is 79%, so the schema already documents most parameters. The description adds value for campaign_id by instructing the agent to chain it from list_campaigns, and the 'Same params as ad account insights' hint may transfer known semantics. However, it does not add per-parameter detail beyond what the schema provides.

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 states a specific verb and resource ('Get campaign insights') and immediately clarifies the scope: 'scoped to one campaign.' This distinguishes it from account-, ad-group-, and ad-level insight tools, and the reference to 'Same params as ad account insights' reinforces its identity.

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?

The description provides explicit chaining guidance ('Chain from list_campaigns -> campaign_id') and contrasts with ad account insights, which implies when the account-level variant is appropriate. It could be stronger by naming the alternative tool directly and stating exclusions for ad-group/ad-level insights, but the usage context is clear.

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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