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

With no annotations provided, the description carries full behavioral burden. It discloses that this is 'Real Google web search' and enumerates output components (top 10 organic results, answer box, knowledge graph). It also notes the pricing model and payment method. However, it does not mention rate limits, auth requirements, or behavior around edge cases (e.g., empty results), leaving room for improvement.

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 compact and front-loads the core action. It mixes useful details (result contents, trigger phrases) with moderately relevant metadata (tier, cost, payment). The structure is clear, though the pricing/payment line could be considered secondary information for a tool selector.

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?

This is a simple single-parameter tool with no output schema, so the description does well to explain both input semantics ('For a query') and expected output ('top 10 organic results, answer box and knowledge graph'). It also provides pricing context and usage triggers. Missing details like return field structure or optional gl/hl handling are minor for such a straightforward tool.

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 input schema has 0% description coverage, so the description must compensate. It indicates that 'q' is the query text via the phrase 'Query: ?q=&gl=&hl=—', which adds some meaning. Yet it also introduces gl and hl as possible parameters without explaining them, and these are absent from the schema. The description clarifies the primary parameter but leaves ambiguity about the others.

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 opens with a specific verb and resource: 'Get ranked web results for a query.' It further clarifies scope with 'top 10 organic results, answer box and knowledge graph, in one call,' which distinguishes it from sibling tools like search_news, search_sources, and social_search.

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 provides explicit trigger phrases: 'Use when asked: "search the web for x", "look up pages about a topic", "google this for me".' It does not explicitly name alternatives or when-not-to-use cases, but the usage context is clear and specific for this tool.

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