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generate_ppt

Create professional PowerPoint presentations from natural language descriptions. Ideal for pitch decks, training materials, or business reviews.

Instructions

Generate a professional PowerPoint presentation (.pptx) from natural language. The AI creates structured slide content with titles, bullet points, and visual suggestions. Use this when you need presentation slides, pitch decks, or training materials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesThe presentation topic, e.g. 'AI Trends 2026', 'Q2 Business Review', 'Product Launch Plan'
requirementsYesDetailed requirements: target audience, key points, tone, slide count preference
slide_countNoApproximate number of slides (5-30). Default: 10.
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It states the AI creates structured slide content with titles, bullet points, and visual suggestions, which gives basic behavioral insight. However, it does not disclose constraints, output handling, or potential side effects, leaving some gaps.

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?

The description is two sentences long with no wasted words. The first sentence states the core function and output format, and the second explains the AI's role and usage guidance. Every sentence serves a clear purpose.

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

Completeness4/5

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

Given 3 parameters and no output schema, the description covers the essential purpose and usage. It explains what the tool creates and when to use it. It could be more complete by mentioning how the result is returned (e.g., file download or link), but overall it is sufficient for agent understanding.

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%, with each parameter already described. The description adds general context (e.g., 'from natural language') but does not provide parameter-specific details beyond what the schema already offers. As baseline, this is adequate.

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 clearly states the tool generates a PowerPoint presentation (.pptx) from natural language, and mentions creating structured slide content. It also provides specific use cases (presentation slides, pitch decks, training materials), distinguishing it from sibling tools like generate_code, generate_excel, and generate_word.

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?

The description includes explicit usage guidance: 'Use this when you need presentation slides, pitch decks, or training materials.' This clearly indicates when to use the tool. However, it does not provide explicit negative examples or alternatives beyond what sibling names imply.

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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