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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is the output shape: Markdown, one heading per question. That is genuinely useful for parsing results. It does not discuss size, pagination, or freshness of the FAQ, which is a minor gap for a static-content tool.

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?

Three short sentences: purpose and scope first, usage directive second, return format last. No filler, no restatement of the title, and the topic list is compact enough to scan.

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 zero-parameter, read-only reference tool with no output schema, the definition supplies everything needed: what content it returns, how it is formatted, and when to consult it. Nothing an agent needs before invoking it is absent.

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?

The tool takes zero parameters, so the baseline of 4 applies; there is no argument meaning to clarify. The description correctly implies a parameterless, fixed-topic lookup.

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 the answers to common questions') and enumerates the exact topics covered: price, safety and approvals, API keys, multiple ad accounts, supported AI apps. That topical enumeration plus the Markdown return format clearly distinguishes it from siblings like get_setup_guide or get_example_prompts.

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?

Gives an explicit trigger condition: 'Use this before answering such a question from memory,' which tells the agent when this tool beats its own knowledge. It stops short of naming when not to use it or pointing to a specific sibling for setup/example content, so routing among the other get_* tools is left implicit.

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