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Apogee: Bulk Ad Launcher for Meta, TikTok & Snapchat

Meta winners and losers

get_top_performers
Read-onlyIdempotent

Rank a Meta account's ads or ad sets by a metric: what to scale, what to cut. Get top and worst performing ads/adsets ranked by a metric. Perfect for "what is working" or "what should I scale/kill" questions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "date_preset": "<date_preset>",
      "metric": "<metric>",
      "level": "<level>",
      "ad_account_id": "<ad_account_id>"
    },
    "name": "get_top_performers"
  }
}

Input Schema

NameRequiredDescriptionDefault
levelYesLevel to analyze
limitNo
metricYesMetric to rank by
date_presetYes
ad_account_idYesMeta ad account id (act_…), from list_ad_accounts

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds that results include both top and worst performers, which is useful ordering context. It does not explain what limit does, whether results are truncated, or anything about the return shape, leaving gaps beyond annotations.

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

Conciseness3/5

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

Two sentences say substantially the same thing: 'Rank ... by a metric' and 'Get top and worst performing ... ranked by a metric.' The quoted use cases are helpful, but the repeated ranking statement wastes space and the description is not front-loaded with anything beyond the purpose.

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

Completeness3/5

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

With no output schema, five parameters, and only 60% schema coverage, the description should do more to explain limit, date_preset, and the campaign-level option. It is adequate for understanding the tool's purpose but not complete enough to invoke it confidently without inspecting the schema.

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

Parameters2/5

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

Schema description coverage is only 60%: limit and date_preset have no schema descriptions, and the description does not compensate for either. It does mirror the metric-ranking idea, but it also says 'ads or ad sets' while the level enum includes campaign, creating a mismatch rather than clarifying the level parameter.

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 states a specific verb and resource: ranking a Meta account's ads/ad sets by a metric, plus the scale/cut framing. It does not, however, distinguish itself from the sibling get_platform_top_performers, so an agent cannot tell from this text alone which top-performers tool to pick.

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?

It offers implied usage via the quoted questions ("what is working", "what should I scale/kill"), which gives an agent a scenario. But there is no explicit when-not guidance, no named alternatives (e.g., breakdown tools or get_platform_top_performers), and no note on whether this replaces or complements get_platform_performance.

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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