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 genuinely new behavior: the `{ ok: false, error }` failure shape and the instruction not to retry blindly. However, it stays silent on the mutation-flavored parameters it accepts (replaceExisting, keptPrompts) and on what a successful response contains, which matters given no output schema.

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 sentences, front-loaded with the purpose and no filler. The second sentence is long but each clause (explain plainly, ask the user, don't retry) carries actionable instruction.

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 description covers the purpose and the failure path, which is more than many tools do. But with 11 parameters at 18% schema coverage and no output schema, key semantics — generation volume, funnel mixing, prompt replacement, language — are left entirely undocumented.

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 only 18% across 11 parameters, and the description mentions none of them. Nothing explains topics vs promptsPerTopic vs limit, the funnelMix object, keptPrompts, or what replaceExisting changes — the agent must infer all of this from bare property names. Only the 'select a valid project' aside hints at advertiserProjectId.

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 ('Generate suggested user-style prompts') and scopes it to 'AI Visibility monitoring based on selected topics and project context'. It is distinguishable from siblings like add-llm-prompt or classify-llm-prompts, though it never names an alternative to sharpen the boundary with get-llm-prompt-task-suggestions.

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?

Usage is only implied by the phrase 'based on selected topics and project context'; there is no statement of when to call this versus add-llm-prompts or get-llm-prompt-task-suggestions, nor prerequisites such as needing an existing project. The error-handling sentence does give useful reactive guidance (explain the error, ask the user, don't blindly retry) but that is post-failure behavior, not invocation guidance.

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