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AxelVerneBooks

marketing-scope-mcp

Plan a campaign

plan_campaign
Read-onlyIdempotent

Turn a campaign objective into a pre-spend plan: set scoreable tactics, offer targets, channel targets, anti-targets, and kill criteria.

Instructions

Turn a campaign objective into a pre-spend plan: offer targets, channel targets, anti-targets (budget black holes), and kill criteria. Purpose: decompose a marketing goal into scoreable tactics BEFORE any spend. Use this before score_offer on any new product/launch; re-plan only when kill criteria trigger. Sibling distinction: score_offer grades ONE offer statement; this plans the whole campaign strategy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
objectiveYesWhat the campaign must accomplish, e.g. 'sell 30 copies of the build manual in 30 days'
audience_hintsNoWhere the audience already gathers, e.g. ['r/sysadmin', 'EMT Facebook groups', 'existing email list']

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful non-annotation context: this is a pre-spend planning step whose outputs (targets, anti-targets, kill criteria) drive later scoring, and re-planning is gated on kill criteria. It stops short of describing how the plan is returned or how scoreable tactics are structured.

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?

Front-loads the core action and its outputs, then layers purpose, usage, and sibling routing. Dense but every clause carries routing or scope information; the parenthetical labels ('budget black holes') add slight bulk without new meaning.

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 no output schema, the description usefully enumerates what the plan contains and when it is consumed, which is enough for correct invocation. It does not address the other siblings (build_plan, check_plan), leaving a minor gap in the workflow picture.

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% and both parameters are documented with examples in the schema itself. The description does not add format, syntax, or constraint detail beyond what the schema provides, so the baseline of 3 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?

States a specific verb+resource (turn a campaign objective into a pre-spend plan) and enumerates the concrete artifacts produced (offer targets, channel targets, anti-targets, kill criteria). It explicitly separates itself from score_offer, so an agent can route correctly without opening 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 Guidelines5/5

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

Gives explicit timing ('before score_offer on any new product/launch') and an explicit re-use condition ('re-plan only when kill criteria trigger'). It also names the alternative tool and the boundary condition that selects between them, leaving nothing to inference.

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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