Skip to main content
Glama
HYPD-AI

HYPD AI - OpenAI Ads

by HYPD-AI

Get ad insights

get_ad_insights
Read-only

Retrieve performance insights for a single ad, including impressions, clicks, spend, CTR, CPC, and CPM. Sort and limit results to rank ads by key metrics.

Instructions

Retrieve performance insights for a single ad. 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_idYesThe ID of the ad 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?

Annotations (readOnlyHint, openWorldHint) indicate it's a safe, non-destructive operation. The description adds value by detailing pagination (first_id/last_id/has_more) and emphasizing that monetary metrics are in account currency as decimals, not micros, which is beyond the annotations.

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 concise (one paragraph, ~100 words) and front-loaded with the main purpose. Every sentence adds value: output structure, paging, fields, ranking usage, and currency note. No wasted words.

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 and no output schema, the description adequately explains the output format and paging. It mentions key fields that can be projected but omits full detail; however, the complexity is well-covered for a read-only insights tool.

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

Parameters4/5

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

Schema description coverage is 100%, baselined at 3. The description adds meaning by explaining how to combine aggregation_level, sort, and limit to rank entities, and clarifies monetary metric format, going beyond the parameter descriptions.

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, specifies the output as a list with paging, and lists projected fields. It uses a specific verb and resource, and the name distinguishes it from sibling tools like get_ad or get_campaign_insights.

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 ad performance with aggregation, sort, and limit, but it does not explicitly state when to use this tool versus alternatives or provide exclusion criteria. The guidance is implicit rather than direct.

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/HYPD-AI/openai-ads-mcp'

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