aeo_generate_prompts

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds real value beyond them by disclosing that 'The topic and existing prompts are sent to OpenAI' — a third-party data transmission fact an agent cannot get from structured fields — and by noting the intent-balancing and dedup behavior of the output. It omits cost/latency, whether results are persisted, and the shape of the response, which keeps this at a 3.

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?

Two short sentences, front-loaded with the action and its effect. The bracketed '[Provider: OpenAI]' line is redundant with 'sent to OpenAI' in the preceding sentence and is the only wasted text.

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?

With five parameters at 0% schema coverage and no output schema, the description should explain what comes back and what the required/optional parameters control. It does neither for target_count, primary_intent, or brand, and never states the return value (presumably a list of prompt strings), so an agent cannot call this correctly without guessing.

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% across five parameters, so the description must carry the full load. It only explains topic and existing_prompts; brand, target_count (default 20), and primary_intent are left entirely undefined — notably primary_intent, which interacts with the claimed 'intent-balanced' behavior but has no enumerated or explained values.

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 gives a specific verb and resource — 'Propose additional natural-language AEO prompts for a topic' — plus two differentiating qualifiers ('intent-balanced + deduped'). It does not name any sibling such as aeo_audit_prompts or add_tracked_prompts, so the agent must infer that this generates ideas rather than auditing or persisting them.

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?

There is no explicit when-to-use guidance and no exclusions. The word 'additional' and the presence of an 'existing_prompts' parameter imply this is for extending an existing prompt set rather than creating one from scratch, but the agent has to construct that rule itself, and nothing says when to prefer this over add_tracked_prompts or aeo_cluster_prompts.

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