google_serp_serp_light: GET /

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

With no annotations provided, the description carries the full burden, and it does disclose key traits: it omits rich blocks, returns only organic results, and supports specific filters. However, it doesn't mention error handling, rate limits, or potential staleness of data—common concerns for scraping tools. It adds value but isn't exhaustive.

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 well-structured and front-loaded: it states the core purpose, then omissions, capabilities, return format, and use cases. Every sentence contributes value, but it's slightly long given the detailed schema already available. Still, no fluff.

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?

Given the 12 parameters, detailed schema, and no output schema, the description covers the essential decision-making info: what it returns, key filtering options, and typical use cases. It doesn't explicitly explain pagination mechanics (though schema does) or edge cases, but the provided context is sufficient for an agent to select and invoke it correctly.

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 baseline is 3, but the description groups parameters into meaningful categories (location/uule, country, language, filters, pagination), giving agents a high-level understanding of how they combine. It adds conceptual clarity beyond the schema's individual parameter descriptions.

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 is a lightweight Google Search scraper that returns only organic results, explicitly listing what it omits (AI Overview, knowledge graph, PAA, etc.) and what it returns (title, link, snippet, position). This makes it readily distinguishable from siblings like serp_getSearchResults or news/shopping 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?

Explicit use cases are given: high-volume keyword monitoring, bulk rank tracking, backlink discovery, and any workflow where only the ten blue links matter. This implies when not to use it (when rich SERP blocks are needed), though it doesn't explicitly name the alternative tool like hasdata_google_serp_serp_getSearchResults. Clear context but no formal exclusion.

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