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Green-pep

meta-ads-mcp-patched

by Green-pep

get_ad_insights

Retrieve key performance metrics for a specific ad, such as impressions, clicks, spend, and conversions, to evaluate and optimize ad performance.

Instructions

Get performance insights for a specific ad.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ad_idYesAd ID
levelNoAggregation level: campaign, adset, ad
fieldsNoComma-separated insight fieldsimpressions,clicks,spend,reach,frequency,cpc,cpm,ctr,actions,cost_per_action_type
filteringNoJSON string for filtering
breakdownsNoBreakdown dimensions: age,gender,country,region,placement,device_platform
time_rangeNoJSON string {since,until} in YYYY-MM-DD format
date_presetNoDate preset: TODAY,YESTERDAY,LAST_7D,LAST_14D,LAST_30D,THIS_MONTH,LAST_MONTH,THIS_QUARTER,LAST_QUARTER,THIS_YEAR,LAST_YEAR
time_incrementNoTime granularity: all_days, 1, 7, monthly
Behavior2/5

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

No annotations are provided, and the description adds almost no behavioral context. It only states 'Get performance insights' without disclosing return format, pagination, rate limits, or any side effects. This is a minimal, read-only-like description that does not compensate for the lack of 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 eight-word sentence that is perfectly concise and front-loaded. Every word contributes to stating the tool's primary purpose with no redundancy or filler.

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

Completeness2/5

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

Given the tool has 8 parameters, no annotations, and no output schema, the description is far too sparse. It does not mention the tool's capabilities around filtering, breakdowns, date ranges, or the types of insights returned, leaving the agent to infer almost everything from the schema.

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 100%, so the input schema already documents all eight parameters. The description does not add any parameter-level meaning beyond what the schema provides, and the baseline for high coverage is 3.

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 uses a specific verb ('Get'), identifies the resource ('ad'), and specifies the scope ('specific'), clearly distinguishing it from sibling tools like get_campaign_insights or get_adset_insights. It explicitly targets a single ad's performance 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?

Usage is implied: use when you need performance insights for a specific ad. However, it does not explicitly mention when not to use it or alternatives, such as using account-level or campaign-level insights, despite having several sibling insight tools.

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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