Skip to main content
Glama

Cross-Platform Performance Report

ads_report
Read-onlyIdempotent

Aggregate performance metrics from Google Ads and Meta Ads into a single unified view. Filter by platform, campaigns, and sort by spend, ROAS, or conversions.

Instructions

Aggregate performance metrics across Google Ads and Meta Ads into a single unified view. Input: date_range ({start, end} as YYYY-MM-DD, defaults to the last 7 days), optional platform filter, optional campaign_ids filter, optional sort_by ("spend"|"roas"|"conversions"|"ctr"|"cpc"), and limit. Returns {period, totals (spend, impressions, clicks, conversions, revenue, ROAS, CPC, CTR), by_platform, campaigns[] (sorted per sort_by), top_performers, underperformers}. This is the entry point for most analysis workflows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformNoFilter by platform
date_rangeNoDefaults to last 7 days
campaign_idsNoFilter specific campaigns
sort_byNospend
limitNo
Behavior4/5

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

Annotations already indicate readOnly, non-destructive, idempotent behavior. The description adds value by detailing the return structure (period, totals, campaigns, top_performers, etc.) without contradicting 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 a single, well-structured paragraph with purpose first, then input, then output. 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?

For a 5-param tool with no output schema, the description covers inputs, outputs, and usage context. However, 'top_performers' and 'underperformers' are not explained, leaving minor ambiguity.

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?

The description explains the date_range format with defaults, lists sort_by options, and mentions limit. This adds context beyond the schema's 60% coverage, especially for the return shape that connects to parameters.

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 tool's purpose: 'Aggregate performance metrics across Google Ads and Meta Ads into a single unified view.' This is a specific verb-resource combination, and the tool stands out from siblings like campaign_list or budget_analyze.

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 notes 'This is the entry point for most analysis workflows,' which implies broad usage but does not explicitly list when not to use it or provide alternatives.

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/enzoemir1/adops-mcp'

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