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

The description discloses important behaviors beyond the annotations: it costs credits, and re-querying the same keyword set within a week is free. It also explains that omitting location_code yields worldwide volume while difficulty is computed for the US. These details align with annotations (readOnlyHint=false, destructiveHint=false) and add valuable context without contradiction.

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 a single dense paragraph but well-structured: it opens with the primary function, then usage guidance, then parameter/behavior details, then cost. It is slightly long but each sentence adds value; no fluff. It earns a 4 rather than a 5 because of the density of clauses, though it remains clear.

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 main aspects needed to use the tool correctly: what data is returned, when to use it, parameter variations, and cost behavior. Since no output schema is provided, the description's mention of the returned fields (search volume, CPC, competition, trend, difficulty) partially compensates. It lacks explicit error or edge-case handling, but that is beyond typical expectations.

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% for both parameters, and the description enriches them: keywords are clarified as 'up to 10 search phrases' with an example, and location_code provides a concrete list of market codes. The added explanation of worldwide vs. country-specific behavior goes beyond the schema, fully clarifying parameter semantics.

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 clearly states the tool returns monthly search volume, CPC, competition, 12-month trend, and keyword difficulty for up to 10 keywords, naming the data sources (Google Ads Keyword Planner, DataForSEO Labs). This is a specific verb-resource pairing that distinguishes it from sibling tools like research_backlinks or research_domain_overview.

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?

Explicitly states when to use: 'Use when the user asks how often something is searched or how hard it is to rank, or to size a keyword before writing a page.' Also provides parameter usage guidance, explaining how to omit location_code for worldwide results and how to pass a country code, leaving no ambiguity about invocation scenarios.

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