create_carousel

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

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits. It explains the three distinct processing modes, fallback behaviors when extraction fails, orchestration workflows for topic-only inputs, platform-specific outputs, and post-rendering suggestions. The only minor gap is not explicitly mentioning rate limits or authentication requirements.

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

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

The description is well-structured with clear sections (modes, workflows, platforms, post-rendering) and uses bullet points effectively. While comprehensive, it's appropriately sized for a complex 8-parameter tool with multiple operational modes. Every sentence serves a purpose in clarifying usage.

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

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

Given the tool's complexity (8 parameters, 3 distinct modes, multiple workflows) and no annotations or output schema, the description provides exceptional completeness. It covers all operational scenarios, explains behavioral outcomes, provides usage examples, mentions platform specifics, and even suggests follow-up actions. This fully compensates for the lack of structured metadata.

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

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

With 100% schema description coverage, the baseline is 3, but the description adds significant value by explaining how parameters interact in the three modes. It clarifies that content and sourceUrl are mutually exclusive alternatives, topic triggers research workflows, and platform affects output format. This contextual understanding goes beyond the schema's individual parameter descriptions.

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

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

The description explicitly states the tool's purpose as a 'full pipeline' that transforms content into slides and PDF/PNG outputs. It clearly distinguishes from sibling tools like create_template, list_templates, preview_slides, and render_slides by being the comprehensive end-to-end solution rather than individual components.

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

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

The description provides extensive guidance on when to use each input mode (content, sourceUrl, topic) and includes specific workflow examples. It explicitly mentions alternatives like firecrawl_scrape, web_fetch, gemini_deep_research, and supadata_transcript for different scenarios, giving clear context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.