generate_slideshow

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the async nature ('Rendering is async (~45s)') and the AI-driven selection of text/images/styling, which are important behavioral traits. It does not mention potential side effects, permissions, or failure modes, but the disclosed information is valuable and not redundant.

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 compact and front-loaded, with the main purpose in the first sentence, followed by the async note and then a clearly formatted Args section. Every sentence is purposeful, with no filler or repetition.

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?

For a 2-parameter tool with no output schema, the description covers the core functionality, parameter semantics, and the next step (polling slideshow_status). It does not specify the initial response format or error handling, but given the tool's simplicity and the async pointer, it is reasonably complete.

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?

Schema description coverage is 0%, so the description must fully explain parameters. The 'Args' section does this well: it explains additional_context (controls topic, slide count, text, fonts, tone, etc.) and images (optional background URLs, 0-indexed mapping). This adds significant meaning beyond the bare schema names and types.

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 clearly states the tool's function: 'Generate a slideshow from a natural-language prompt.' It also adds a distinguishing detail, 'AI picks text, images, and styling,' which separates it from sibling tools like create_slideshow by emphasizing the AI-driven generation from a prompt.

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 implies usage (provide a natural-language prompt and optionally images) and gives a post-usage instruction ('Poll slideshow_status to track progress'), but it does not explicitly differentiate when to use this tool versus the sibling create_slideshow or other slideshow tools. There are no exclusions or alternative recommendations.

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