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

Annotations already mark it read-only, idempotent and open-world, and the description adds substantial context beyond that: $0.04 cost, x402 USDC-on-Base payment via _meta["x402/payment"], empty result sets still being charged, bad input being free, and upstream errors not billed. That is exactly the billing/failure behavior an agent cannot get from annotations or schema, and nothing contradicts the hints.

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?

Purpose and the metrics it returns are front-loaded and the pricing/edge-case notes follow in a logical order. There is mild redundancy between 'up to 100 ideas in one $0.04 call' and the later 'Price: $0.04 per successful call', but each sentence otherwise carries information.

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 no output schema, the description takes on the job of describing the response (volume, CPC, competition, difficulty, intent) and also covers cost, payment mechanics and the empty-result/free-400/uncharged-error cases. An agent has enough to decide whether to call and how to pay correctly.

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 100%, so the parameters (limit, country, locationCode, languageCode, includeMonthly) are already fully documented and the baseline of 3 applies. The description's metric glossary (volume, cpc, competition 0-1, difficulty 0-100) explains return values rather than adding parameter meaning, so it doesn't push this above baseline.

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+resource ('Keyword ideas for a seed keyword') and enumerates the returned metrics, plus a count/price bound. It implies differentiation from volume-lookup siblings via 'Use when you need related keywords to target' but never names keyword_overview or keyword_search_volume, so the boundary is inferred rather than stated.

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 one clear usage cue ('Use when you need related keywords to target'), which positions it as an expansion/discovery tool. However, no sibling is named as an alternative and no when-not-to-use condition is given, even though keyword_search_volume and keyword_overview overlap conceptually.

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