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Pitch Deck Visual Generator - ManyMotions

Prepare Pitch Deck

prepare_pitch_deck

Prepare six pitch deck slide visuals with ManyMotions from a startup: problem, solution, market, product, business model and the ask, designed as one deck and returned as images. Returns the settings and the credits required. Nothing is generated and no credits are spent. No sign-in is needed to prepare. Slide visuals from the user's own startup description only: do not use it for uploaded decks, logos or images, and do not put other companies' logos or trademarks on the slides.

Input Schema

NameRequiredDescriptionDefault
marketYesThe target market and customers.
problemYesThe problem it solves.
startupYesWhat the startup does and its product.
business_modelYesHow it makes money.

Output Schema

NameRequiredDescriptionDefault
runNo
stateYes
balanceNo
messageYes
outputsNo
projectYes
dashboard_urlYes
credits_requiredNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the annotations, it discloses that nothing is generated, no credits are spent, no sign-in is required, and that the response carries the settings and the credit cost. This is high-value context an agent needs before committing to the call, particularly given the absence of a read-only annotation.

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 what is produced, followed by return behavior and constraints. Every sentence carries information, though the constraint clause is packed into one long sentence that could be split for scannability.

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 four-input, non-destructive preparation tool, the description covers what is produced, what is returned, cost/sign-in side effects, and input restrictions. Even though an output schema exists, the description's summary of the return shape is accurate and not contradictory.

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%, so each of the four required inputs is already documented, and the description adds little per-parameter meaning. It does clarify that content comes from the user's own startup description, but it also names slides (solution, product, ask) that have no corresponding parameters, which is mildly ambiguous rather than helpful.

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 states a specific verb ('prepare'), a precisely scoped resource ('six pitch deck slide visuals... problem, solution, market, product, business model and the ask'), the engine used (ManyMotions), and the return form (images). An agent can tell this apart from the generate/get siblings without opening any schema.

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

Usage Guidelines4/5

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

It gives clear positive and negative usage conditions: only from the user's own startup description, not for uploaded decks, logos or images, and no third-party logos or trademarks. The only gap is that it never routes to the sibling tools (generate_result/get_result), so the agent must infer the follow-up step.

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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