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Ask Toffu (Marketing Agent)

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Delegate any marketing task or question to Toffu, the company's AI marketing agent. It acts on the company's connected accounts: pull analytics, diagnose performance drops and trends, create and edit campaigns, ad sets, ads and audiences (with approval), create/publish content, build reports. Use for anything beyond raw campaign metrics. Long tasks emit progress; final answer returns when done.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe task or question, in plain language
session_idNoOmit on your first message, one is created and returned. Only to continue an earlier conversation, pass the session_id from that conversation's response.new

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations declare readOnlyHint=false, openWorldHint=true, destructiveHint=false, so the safety envelope is already partly covered. The description adds genuinely useful context beyond that: mutations require approval, the agent acts on the company's connected accounts, and long tasks emit progress before a final answer. It stops short of stating what persists or how approval is granted.

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 core purpose and the sibling-distinguishing rule are front-loaded, and the capability list is packed but relevant to scoping. It runs slightly long and the capability enumeration is dense, but every clause carries selection-relevant information.

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?

With an output schema present, return values need not be described, and the description still covers capabilities, approval, and progress behavior. The only gap is the unsignposted relationship to get_task_result for async completion, which is a minor completeness miss rather than a blocker.

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 coverage is 100%, so both message and session_id are already fully documented in the schema, including the 'omit on first message' semantics. The description adds nothing about parameter format or usage, so the baseline 3 for a well-covered schema applies.

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 precise verb and resource: delegate a marketing task or question to the Toffu agent, and enumerates the concrete action classes it covers (analytics, diagnosis, campaign/adset/audience edits, content, reports). It explicitly distinguishes itself from the sibling query_campaign_performance by scoping itself to 'anything beyond raw campaign metrics.' An agent can pick this tool without reading either schema.

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

Usage Guidelines4/5

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

It gives an explicit routing rule ('Use for anything beyond raw campaign metrics') and notes that write actions happen 'with approval.' It does not, however, address the get_task_result sibling or explain how the 'progress' emission relates to polling for long-running tasks, leaving a real ambiguity in the when-to-use story.

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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