Skip to main content
Glama

Persuasion Taxonomy

Plan marketing copy (the nine reader questions)

plan_marketing_copy
Read-onlyIdempotent

Plan any piece of marketing copy before you write it, whether it's an ad, a landing page, a sales page or sales letter, an email, a subject line, a social post, a headline or a video script. Give it the goal, the reader and the offer, and it tells you which of the nine questions every reader silently asks this piece has to answer, which ones deserve the most words for this reader, and a few ways to answer each one, drawn from real advertising and linked to the Persuasion Taxonomy. One option is always the established move and the rest are less expected, because left to itself a model answers every question with the move everyone else makes, and readers have learned to skim past it. So call it before you draft, even when you're sure you know how to write the piece, and when the draft is done, check it with diagnose_marketing_copy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYesWhat the copy has to get the reader to do. Use purchase when they should buy now, signup for an opt-in, a trial, a demo or a lead form, click when the whole job is the click (most ads and links), and engagement for nurture emails, newsletters and social posts that should be read, answered or followed.
offerYesWhat you're selling or asking for, and the main promise.
formatYesThe kind of copy it is: ad, landing_page, sales_letter for long-form sales copy, email, email_subject, social_post, video_script or headline.
audienceYesWho will read it, as specifically as you can put it: their role, their situation and what they already believe.
categoryNoThe industry, if you want to compare against what brands in that category usually do. There is enough data for apparel, automotive, b2b_saas, beauty_skincare, business_coaching, consumer_tech, dtc_food_bev, dtc_health, fitness_health, home_goods, info_product, investing, marketing_education, otc_pharma, personal_care, personal_development, supplements, weight_loss. Any other category still works, just without the comparison.
awareness_levelNoHow much the reader already knows, on Eugene Schwartz's scale. Use unaware if they don't know they have the problem, problem_aware if they feel it, solution_aware if they know solutions exist, product_aware if they know you, and most_aware if they're ready and only need the offer.
persuasion_modeNoHow hard the copy is allowed to push. Balanced is the default, persuasive and sustainable over time. Equity protects long-term trust, so it rules out fear, hype and hard-sell moves. Aggressive is for short-term direct response and allows fear, threat and hard scarcity. In every mode, the claims stay true.balanced
options_per_questionNoHow many ways to answer each question you want to see. The default is 4.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), so the bar is lower. The description adds genuine behavioral context beyond them: it explains what the output contains (which of nine questions to answer, weight per reader, several answer options), that one option is always the established move, and the rationale (models default to overused moves that readers skim past).

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-loaded with purpose, then usage, then the rationale for the 'one established move' design. It is on the long side and the opening format enumeration is list-heavy, but nearly every sentence carries routing or behavioral information rather than filler.

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?

For a planning tool with no output schema, the description does what the schema can't: it characterizes the return (question list, weighting, multiple candidate answers drawn from real advertising, linked to the Persuasion Taxonomy). Combined with 100% parameter coverage, an agent has everything needed to call it and interpret the result.

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% and each parameter carries its own enum/value documentation, so the schema does the heavy lifting. The description only loosely names 'the goal, the reader and the offer', which maps to a subset of the eight parameters without adding format or syntax detail. Baseline 3 is appropriate.

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 (plan) and resource (marketing copy) up front, then enumerates the covered formats. It explicitly separates itself from the post-draft sibling 'diagnose_marketing_copy', so an agent can route between them without opening a 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 an explicit when-to-use ('call it before you draft, even when you're sure you know how to write the piece') and names the complementary tool and the condition for it ('when the draft is done, check it with diagnose_marketing_copy'). No guidance is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.