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Ballast - Cold Email

Daily time-series email metrics for a campaign or all campaigns

get_campaign_stats
Read-only

Daily time-series email metrics for a campaign or all campaigns. Returns daily time-series counts (day-by-day sent, replied, opened, bounced, positive) for a specific campaign (pass campaignId) or all campaigns combined over the last N days. USE THIS to plot charts or view daily performance trends over time. DO NOT use for high-level workspace summary totals (use get_overview instead) or for multi-dimensional breakdowns by ESP provider, mailbox, or step (use get_campaign_analytics instead).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo7, 30 or 90 days
campaignIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish read-only, non-destructive, closed-world behavior. The description adds value beyond them by enumerating the returned metrics and the time-window scoping, which matters because there is no output schema. It stops short of describing granularity guarantees, timezone/day-boundary handling, or behavior when campaignId is omitted versus invalid, so it is not a 5.

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?

Three tightly packed sentences, front-loaded with purpose and return contents, followed by usage routing. No filler and every clause carries selection-relevant information.

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

Completeness5/5

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

With no output schema, the description takes on the burden of describing return values and does so (day-by-day sent/replied/opened/bounced/positive), plus scope and access pattern (campaign vs all). Annotations cover safety. Nothing essential for correct invocation is missing.

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?

Schema coverage is only 50% (campaignId is undescribed in the schema), so the description must compensate. It does: 'pass campaignId' implies a specific campaign versus omitting it for all campaigns combined, and 'over the last N days' explains the days window. It does not explain valid range, non-7/30/90 values, or invalid-ID handling.

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?

States a specific resource and scope: daily time-series counts (sent, replied, opened, bounced, positive) for one campaign or all campaigns over N days. It explicitly names the two sibling tools it is not (get_overview, get_campaign_analytics), so an agent can disambiguate without opening schemas.

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?

Explicit USE THIS case (plotting charts, viewing daily trends over time) and explicit DO NOT cases with named alternatives for both workspace-level totals and multi-dimensional breakdowns. When/when-not/alternatives are all covered.

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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