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generate_ad_copy_blueprint

Generates high-CTR ad copy variations for Meta, Google, Twitter, and LinkedIn using a Hook-Problem-Solution-CTA structure to improve campaign performance.

Instructions

Generates high-CTR Meta, Google, and Twitter ad copy variations (Hook -> Problem -> Solution -> CTA).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformYesAd platform target
offer_summaryYesSummary of the offer or product being advertised
Behavior2/5

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

No annotations are supplied, so the description carries the full burden of behavioral disclosure. It mentions 'Generates' and 'high-CTR' but does not explain whether the operation is non-destructive, what the output format looks like, how many variations are returned, or any rate/limits. The description offers minimal behavioral insight beyond the verb.

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?

A single sentence with no filler, front-loads the core purpose, and packs the structural framework into a compact parenthetical. Every word earns its place.

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?

Given the absence of an output schema and annotations, the description should describe the return shape and clarify platform coverage. It does neither, and it contradicts the platform enum. The tool is simple, but the description still leaves meaningful gaps 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 coverage is 100%, so the schema already documents both parameters. The description adds the copy-structure detail, which is useful for understanding what offer_summary should contain, but it actively misrepresents the platform parameter by listing only Meta, Google, and Twitter while the enum includes linkedin_b2b. This is a misleading semantic contribution.

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 states a specific verb ('Generates') and resource ('Meta, Google, and Twitter ad copy variations') and gives a clear structural breakdown (Hook -> Problem -> Solution -> CTA), which is helpful. However, it omits LinkedIn from the platform list even though the schema's enum includes linkedin_b2b, creating an inconsistency that blurs the tool's scope.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus its many siblings such as generate_marketing_copy_blueprint, generate_hormozi_offer_blueprint, or generate_brand_positioning_matrix. No conditions, exclusions, or alternative routing are provided, leaving the agent to infer when this specific ad-copy generator is appropriate.

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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