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generate_hormozi_offer_blueprint

Create a high-converting offer blueprint using the $100M Offers framework, boosting dream outcome and perceived likelihood while reducing time and effort.

Instructions

Generates an Alex Hormozi Grand Slam Offer Blueprint ($100M Offers framework) multiplying Dream Outcome & Perceived Likelihood while minimizing Time Delay & Effort.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
core_outcomeYesThe ultimate dream outcome desired by the customer
product_nameYesName of product or service
guarantee_typeNoType of risk-reversal guarantee (e.g. '30-Day Money Back', 'Pay Only On Results')
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It only says 'generates a blueprint' but does not disclose what the blueprint contains, its format, length, or any side effects. Since there is no output schema, the agent has no idea what the return value will look like. The description mentions the framework's value levers but not the tool's actual behavior or limitations.

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 description is a single sentence with minimal waste. It front-loads the tool's purpose and key framework concepts. However, it includes specialized jargon ('Grand Slam', 'Dream Outcome', 'Perceived Likelihood') that may reduce clarity for agents unfamiliar with Hormozi's terminology, so it is concise but slightly dense.

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 there is no output schema and no annotations, the description should explain what the generated blueprint includes, its structure, and how the agent should handle the result. It currently only states the high-level purpose. Missing details like optional parameter behavior (guarantee_type) and expected return format make it insufficient for a tool with moderate complexity.

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%, so the parameters are already well documented. The description adds conceptual context (Dream Outcome, Risk-Reversal) that maps loosely to core_outcome and guarantee_type, but it does not provide additional syntax, enumeration, or formatting details beyond the schema. This meets the baseline for full schema coverage.

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 uses a specific verb ('Generates') with a precise resource ('Alex Hormozi Grand Slam Offer Blueprint') and names the underlying framework ($100M Offers). It clearly distinguishes itself from sibling blueprint generators by referencing Hormozi's specific concepts (Dream Outcome, Perceived Likelihood, Time Delay, Effort), so an agent can tell it apart from generic marketing or pricing blueprint tools.

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?

The description implies usage for Hormozi-style offer creation but does not explicitly state when to choose this tool over alternatives like generate_pricing_tier_blueprint or generate_marketing_copy_blueprint. There is no exclusions or alternative routing. The agent must infer the appropriate context from the framework mentioned, which is adequate but not explicit.

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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