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

Beyond the read-only and idempotent annotations, the description discloses pricing, which failures are charged, missing-keyword behavior, and the x402 payment mechanism. This is unusually complete behavioral context for a paid data-lookup 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?

The description is dense and front-loads the core purpose, metrics, and scope. Every sentence carries useful information, though the pricing and payment details make it heavier than strictly necessary for selection.

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 supplies the metric meanings and billing/missing-data behavior an agent needs to call the tool correctly. Annotations already cover safety, and the description complements them with cost and failure-mode details.

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 coverage is 100%, so the schema already fully documents keywords, country, lang, and includeMonthly. The description adds metric definitions for returned fields and repeats the 20-keyword limit, but adds little parameter-specific meaning beyond the schema; 'comma-separated keywords' also slightly mismatches the array parameter.

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 names the exact resource and metrics (Google search volume, CPC, competition, keyword difficulty and intent) and the concrete scope (up to 20 keywords in one GET). It also explicitly distinguishes itself from keyword_overview, which handles up to 100 keywords via POST.

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?

It states when to use it: 'when you need monthly search volume for a few keywords in a country.' It also names the alternative for larger batches and the condition that selects it, leaving little ambiguity.

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