Suggest Prompts

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: what each surface produces, that source_ids scopes to specific sources with 'omit for all', and how the returned prompts are consumed. It stops short of noting rate limits or auth needs, but with annotations carrying the safety burden this is solid.

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?

Front-loaded with purpose and accepted input, then a bulleted list whose bullets each earn their place by defining an enum value. The closing 'Related' sentence is compact and adds routing value rather than padding.

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?

An output schema exists, so return values need not be spelled out, yet the definition still clarifies that each result is a ready-to-send instruction. Combined with full enum coverage, downstream routing, and the sibling alternative, nothing an agent needs to call this correctly is missing.

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 carry the load and it does: it enumerates every enum value of 'surface' with a plain-language meaning, notes 'notebook' accepts a name or ID, explains source_ids as an optional scope, and describes query as an optional steering hint. This fully compensates for the empty 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?

States a specific verb and resource ('Get AI-suggested, ready-to-send prompts for a studio surface') and immediately scopes it via the required notebook input. It distinguishes itself from the nearest sibling by contrasting with chat_ask(suggest_followups=true) at the end, so an agent can route without opening either schema.

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?

Explicitly tells the agent that each result is meant to be passed to chat_ask for the 'ask' surface or to studio_generate's 'instructions' for studio formats, giving concrete downstream usage. The 'Related' section names the inline alternative and the condition that selects it ('ask + follow-ups in one call' vs 'standalone selector across every surface').

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