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get_adset_insights

Retrieve performance insights for a specific ad set, including metrics such as impressions, clicks, spend, and actions, with optional age, gender, or region breakdowns and custom date ranges.

Instructions

Get performance insights for a specific ad set.

Input Schema

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

Implementation Reference

  • Handler function for get_adset_insights tool. Takes an adset_id and optional insight params, makes a GET request to Meta Graph API /{adset_id}/insights, and returns the JSON response with rate limit info.
    server.tool(
      "get_adset_insights",
      "Get performance insights for a specific ad set.",
      {
        adset_id: z.string().describe("Ad Set ID"),
        ...insightParams,
      },
      async ({ adset_id, ...params }) => {
        try {
          const { data, rateLimit } = await client.get(`/${adset_id}/insights`, { ...params });
          return { content: [{ type: "text" as const, text: JSON.stringify({ ...data as object, _rateLimit: rateLimit }, null, 2) }] };
        } catch (error) {
          return { content: [{ type: "text" as const, text: `Failed: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
        }
      }
    );
  • Input schema for get_adset_insights. Requires adset_id (string) and accepts all shared insight params (fields, breakdowns, date_preset, time_range, time_increment, filtering, level).
    {
      adset_id: z.string().describe("Ad Set ID"),
      ...insightParams,
    },
  • Registration of the 'get_adset_insights' tool via server.tool() within the registerInsightTools function in insights.ts.
    server.tool(
      "get_adset_insights",
      "Get performance insights for a specific ad set.",
      {
        adset_id: z.string().describe("Ad Set ID"),
        ...insightParams,
      },
      async ({ adset_id, ...params }) => {
        try {
          const { data, rateLimit } = await client.get(`/${adset_id}/insights`, { ...params });
          return { content: [{ type: "text" as const, text: JSON.stringify({ ...data as object, _rateLimit: rateLimit }, null, 2) }] };
        } catch (error) {
          return { content: [{ type: "text" as const, text: `Failed: ${error instanceof Error ? error.message : String(error)}` }], isError: true };
        }
      }
    );
  • Shared insightParams schema object reused by get_adset_insights and other insight tools, defining default fields and optional params like breakdowns, date_preset, time_range, time_increment, filtering, and level.
    const insightParams = {
      fields: z.string().optional().default("impressions,clicks,spend,reach,frequency,cpc,cpm,ctr,actions,cost_per_action_type").describe("Comma-separated insight fields"),
      breakdowns: z.string().optional().describe("Breakdown dimensions: age,gender,country,region,placement,device_platform"),
      date_preset: z.string().optional().describe("Date preset: TODAY,YESTERDAY,LAST_7D,LAST_14D,LAST_30D,THIS_MONTH,LAST_MONTH,THIS_QUARTER,LAST_QUARTER,THIS_YEAR,LAST_YEAR"),
      time_range: z.string().optional().describe("JSON string {since,until} in YYYY-MM-DD format"),
      time_increment: z.string().optional().describe("Time granularity: all_days, 1, 7, monthly"),
      filtering: z.string().optional().describe("JSON string for filtering"),
      level: z.string().optional().describe("Aggregation level: campaign, adset, ad"),
    };

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0

TDQS

C2.7/5.0
Behavior1/5

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

With no annotations, the description carries full responsibility for behavioral disclosure, yet it only restates the basic purpose. It does not mention output format, data scope, permission requirements, rate limits, or any side effects, offering no value beyond the tool name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that is concise and front-loaded with the core purpose. While it is minimal, it does not waste words and is appropriately sized for a simple read operation, though it could benefit from a bit more detail.

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?

This tool has 8 parameters, no output schema, and no annotations, making it fairly complex. The description only states the basic action and does not explain what 'performance insights' includes, how to construct time ranges, or what the response will look like, leaving significant gaps for the agent.

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?

The schema provides thorough descriptions for all 8 parameters, including default fields and valid date presets, giving 100% coverage. The description adds no additional meaning to the parameters, landing at the baseline score for strong schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves performance insights for a specific ad set, using the verb 'get' and the resource 'ad set'. It is clear what the tool does, but it does not explicitly differentiate from sibling tools like get_campaign_insights or get_ad_insights, though the name and 'specific ad set' provide some distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as get_campaign_insights or get_ad_insights. It does not mention excluded use cases or recommend other tools for different aggregation levels, leaving the agent to infer usage solely from the name.

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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