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

Annotations already convey read-only, non-destructive, idempotent behavior. The description adds useful context by stating the structured SERP output, naming the result fields, and showing a realistic call with the API key. There is no contradiction with annotations.

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?

One concise sentence states the purpose and expected output, followed by a compact example. No filler or repetition of schema content; the most important information is front-loaded.

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 and simple flat parameters, the description reasonably explains the returned data format by listing organic results, titles, links, snippets, and related data, plus an example invocation. It could mention external API costs or rate limits, but the low complexity and strong annotations mean the description is largely complete.

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 documents all four parameters (query, country_code, tld, _apiKey) with descriptions. The example in the description illustrates valid values but adds no semantic meaning beyond the schema, so the baseline of 3 applies.

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 action and resource — 'Run a Google search' — and specifies the return value as structured SERP results with organic results, titles, links, snippets, and related data. This clearly distinguishes it from siblings like scraperapi_amazon_search and scraperapi_scrape.

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 gives clear contextual usage: call this when you need Google search results in structured form. It does not explicitly name alternatives or conditions when not to use it, but the Google-search scope is unambiguous and no exclusions are needed.

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