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write_product_copy

Read-only

Write product descriptions, landing page copy, or marketing messages that convert. Uses social proof, loss framing, anchoring, and scarcity — without being manipulative. CONVERT. 20 credits (€0.20 per call).

Input Schema

NameRequiredDescriptionDefault
goalYes
draftYes
audienceNo
session_idNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare a safe, read-only, non-destructive, closed-world operation, so the bar is lower. The description usefully adds cost information ('20 credits, €0.20 per call') and discloses the persuasion techniques used, but says nothing about how the draft is transformed or what constraints apply to the output.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core sentence is front-loaded and efficient, but 'CONVERT.' is pure marketing noise that occupies a line without informing an agent, and the persuasive-technique list is only marginally useful relative to the missing parameter context.

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

Completeness2/5

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

An output schema exists so return values need not be described, but with four undocumented parameters, no usage guidance, and no statement of how inputs shape the generated copy, the definition leaves an agent guessing on the parts that matter for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across four parameters, and the description supplies no compensating meaning for any of them. It never explains what 'draft' is (source text? prior version?), what 'goal' should contain, or what 'audience' and 'session_id' do.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource set — product descriptions, landing-page copy, marketing messages — so an agent can immediately tell it is a copy-generation tool, clearly distinct from the analytics-oriented siblings (predict_churn, optimize_pricing, fix_checkout). It stops short of explicitly differentiating itself from those siblings, which is why it is not a 5.

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

Usage Guidelines3/5

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

Use is only implied by the enumerated artifact types ('product descriptions, landing page copy, or marketing messages'), with no guidance on when to reach for this tool rather than a sibling, no prerequisites, and no stated exclusions. An agent must infer the triggering context.

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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