realtime_product_search/v2

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only lists operations and parameters. It does not mention whether operations are read-only, rate limits, authentication, pagination, or response formats, limiting the agent's understanding of side effects and constraints.

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 with a clear operation list, but it includes filler like 'Complete reference documentation' and 'Includes code examples, data samples, and usage guides' that are not actionable for an AI agent. The core operational content is concise but could be more direct.

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 dispatcher-style tool has seven operations and no output schema, yet the description provides only operation names and required params. It lacks return-value descriptions, error behavior, or usage context, making it incomplete for an agent to fully understand the tool's behavior and results.

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 only defines generic 'operation' and 'args', but the description adds essential operation-specific required parameters (e.g., q for search, product_id for details). This compensates for the schema's lack of per-operation parameter definitions, though it omits optional parameters and value formats.

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 it is a real-time product search API for Google Shopping, covering products, offers, and reviews across major retailers. The specific verb-resource pairing and explicit operation list distinguish it from sibling tools focused on other data sources (e.g., Amazon, Walmart).

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 lists each operation with its required parameters, which guides invocation. However, it does not explicitly state when to choose this tool over alternatives like realtime_amazon_data or real_time_walmart_data, leaving selection based on inferred scope (Google Shopping) rather than explicit guidance.

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