keyword_volumes

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

Annotations already declare readOnlyHint=true and openWorldHint=true, reducing the burden on the description. The description adds a valuable behavioral guarantee: it reports exactly on the terms passed and does not expand or invent anything. This clarifies an important boundary beyond the read-only annotation, though it does not cover edge-case behavior such as handling of unmatched keywords.

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 with no wasted words. The first sentence front-loads what the tool returns, and the second sentence names the sibling and the intended use case. Every clause earns its place.

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 is clear about the tool's core behavior and return type, and an output schema exists to document return values. However, with 0% schema description coverage, key input parameters like geo_target_ids and include_search_partners are left under-explained, which could cause incorrect calls despite the presence of sibling tools like suggest_geo_targets. The gap is moderate.

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 schema has five parameters and zero descriptions, so the description must compensate. It only clarifies the keywords parameter with 'a list of keywords you already have'; geo_target_ids, customer_id, language_id, and include_search_partners receive no semantic explanation beyond their names and defaults. This is insufficient for a low-coverage schema.

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 states a specific verb and resource: it reports average monthly search volume, competition, and bid range for a list of keywords the user already has. It also distinguishes itself from suggest_keywords, making its scope immediately clear to an agent scanning sibling tools.

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?

The description explicitly names suggest_keywords as the alternative and explains the difference: this tool does not expand or invent terms, while suggest_keywords presumably does. It also gives a concrete use case—auditing an existing keyword list—so an agent knows when to choose this tool.

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