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nevent_campaign_report

Read-only

Generate the monthly campaign report of the current brand for a calendar month (year + month). Executes 13 parallel queries in one call: marketing campaign metrics for that month and the previous one, ROI and attribution, revenue, variable costs, 24-month purchase history, transactional campaigns, segments and industry benchmarks. For a single campaign use nevent_get_campaign_insights.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYesCalendar year of the monthly report, e.g. 2026
monthYesCalendar month of the report, 1 (January) to 12 (December)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • removedInput schema / properties / campaignId
      Removed value: -{
      -  "description": "Campaign ID to generate the analytics report for",
      -  "type": "string"
      -}
    • addedInput schema / properties / month
      Added value: +{
      +  "description": "Calendar month of the report, 1 (January) to 12 (December)",
      +  "maximum": 12,
      +  "minimum": 1,
      +  "type": "integer"
      +}
    • removedInput schema / properties / timeRange
      Removed value: -{
      -  "additionalProperties": false,
      -  "description": "Optional time range to restrict report data. Defaults to full campaign lifetime.",
      -  "properties": {
      -    "end": {
      -      "description": "End date in ISO 8601 format, e.g. \"2024-12-31\"",
      -      "type": "string"
      -    },
      -    "granularity": {
      -      "description": "Time bucket granularity (deprecated: use top-level timeGranularity)",
      -      "type": "string"
      -    },
      -    "start": {
      -      "description": "Start date in ISO 8601 format, e.g. \"2024-01-01\"",
      -      "type": "string"
      -    }
      -  },
      -  "required": [
      -    "start",
      -    "end"
      -  ],
      -  "type": "object"
      -}
    • addedInput schema / properties / year
      Added value: +{
      +  "description": "Calendar year of the monthly report, e.g. 2026",
      +  "maximum": 2100,
      +  "minimum": 2000,
      +  "type": "integer"
      +}
    • changedInput schema / required
      Previous value: -[
      -  "campaignId"
      -]New value: +[
      +  "year",
      +  "month"
      +]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond the annotations: it discloses that the tool 'Executes 13 parallel queries in one call' and enumerates the data domains included (marketing campaign metrics, ROI/attribution, revenue, variable costs, 24-month purchase history, transactional campaigns, segments, industry benchmarks). This gives the agent a realistic expectation of the operation's weight and scope. It doesn't mention response size or runtime, but the parallel-query disclosure is meaningful.

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 two sentences with zero waste. The core purpose is front-loaded in the first sentence, the behavioral scope (13 parallel queries) is summarized compactly, and the sibling routing is a single clear sentence at the end. Every sentence earns its place.

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 read-only report tool with 2 fully documented parameters and no output schema, the description is nearly complete. It covers what the report contains, the scope, and the alternative for single-campaign insights. The only minor gap is that it doesn't describe the return format or how the 13 query results are structured, but since there is no output schema and the tool is read-only, this is a modest omission rather than a critical one.

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 schema already fully documents both parameters (year and month) with ranges and examples. The description adds the context that these define the report's calendar month, but it doesn't add meaning beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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 states a specific verb ('Generate'), a specific resource ('monthly campaign report of the current brand'), and a precise scope ('for a calendar month (year + month)'). It also distinguishes itself from the sibling nevent_get_campaign_insights by explicitly saying 'For a single campaign use nevent_get_campaign_insights.' This makes the tool's purpose unmistakable.

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

Usage Guidelines5/5

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

The description explicitly says when to use this tool (for a monthly campaign report covering a calendar month) and when not to (for a single campaign, use nevent_get_campaign_insights). It names the alternative tool directly, giving the agent clear routing guidance.

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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