suggest_prompts

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral context beyond that: results are 'ready-to-send,' they can be passed to specific generators, and source_ids/query affect the output. This goes beyond a bare read-only declaration, though it does not discuss auth or rate limits.

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 a clear opening, a bulleted list for surface options, and a related-tools note. It is longer than average but every sentence adds necessary detail; nothing is redundant.

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?

The tool has rich schema (9 enum values), an output schema, and multiple parameters. The description covers the purpose, parameter meanings, output usage, and a key alternative, providing complete context for correct invocation.

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 carries full responsibility. It explains every parameter: notebook accepts a name or ID, surface has a default and detailed meanings for each enum, source_ids scopes to specific sources (with 'omit for all'), and query steers suggestions. This fully compensates for the missing schema 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 starts with a specific verb and resource: 'Get AI-suggested, ready-to-send prompts for a studio surface.' It clearly distinguishes this tool from siblings by framing it as the standalone selector across every surface, and by listing specific surfaces (ask, audio formats, video formats, quiz/flashcards) and matching generators.

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 explicitly names an alternative ('chat_ask(suggest_followups=true)') and explains when that alternative is appropriate versus this standalone tool. It also states that results can be passed to matching generators, giving clear guidance on how to use the tool.

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