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HYPD-AI

HYPD AI - OpenAI Ads

by HYPD-AI

Get ad group insights

get_ad_group_insights
Read-only

Retrieve performance metrics for a single ad group, including impressions, clicks, spend, CTR, CPC, and CPM. Supports date range, daily aggregation, sorting, and pagination.

Instructions

Retrieve performance insights for a single ad group. Returns a list response (data[] with first_id/last_id/has_more for paging). Each row carries id, start_time, end_time, plus the projected fields such as impressions, clicks, spend, ctr, cpc, cpm, readable_time, campaign_name, ad_group_name, and ad_name. Combine aggregation_level, sort, and limit to rank entities (e.g. the top ad by clicks). Monetary metrics (spend, cpc, cpm) are in the account's currency as decimal values, not micros.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_group_idYesThe ID of the ad group to report on.
sinceNoStart date of the reporting window (inclusive), YYYY-MM-DD. Combined with `until` into a date_range time filter.
untilNoEnd date of the reporting window (inclusive), YYYY-MM-DD. Combined with `since` into a date_range time filter.
time_granularityNoAggregation bucket size: 'daily' for one row per day, or 'none' for a single aggregated row over the whole window.
aggregation_levelNoScope each row is aggregated to (e.g. 'ad' to break results out per ad even when querying a campaign). Combine with `sort` + `limit` to rank entities.
fieldsNoFields to project in each row, e.g. ['ad_id','ad_name','campaign_name','readable_time','impressions','clicks','spend','ctr','cpc','cpm'].
sortNoSort expressions applied in order, e.g. [{ "field": "clicks", "direction": "desc" }] to rank by most clicks.
filtersNoAdvanced filter expressions, passed through to the API as-is.
limitNoMaximum number of rows to return (1-10000).
afterNoPagination cursor: pass `last_id` from a previous page to fetch the next page.
beforeNoPagination cursor: pass `first_id` from a previous page to fetch the previous page.
Behavior4/5

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

The description adds value beyond annotations by explaining the return structure (list with paging) and that monetary metrics are in account currency as decimals, not micros. Annotations already declare readOnlyHint=true, so the description enhances transparency without contradiction.

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?

The description is a concise paragraph with no redundant information. Every sentence adds value: purpose, return structure, field list, usage hints, and formatting edge cases. It is well-organized and front-loaded.

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

Completeness4/5

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

Given 11 parameters, full schema coverage, and no output schema, the description covers the key aspects: return shape, paging, parameter combinations, and monetary formatting. It does not document error cases or prerequisites but is sufficient for a read-only tool.

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

Parameters5/5

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

Schema coverage is 100%, but the description provides additional context on how to combine aggregation_level, sort, and limit for ranking, and clarifies monetary metric formatting. This goes above and beyond the parameter descriptions, adding meaningful guidance.

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 it retrieves performance insights for a single ad group, specifying the verb 'Retrieve' and the resource 'performance insights for a single ad group'. It differentiates from siblings by focusing on ad_group level, not campaign or ad level.

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 implies usage for querying a single ad group's insights, but does not explicitly state when to use this tool versus alternatives like get_ad_insights or get_campaign_insights. It provides some guidance on combining parameters (aggregation_level, sort, limit) but lacks explicit when-not or exclusionary context.

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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