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

With no annotations, the description fully discloses behavioral traits: it is a paid service ($0.004/call) using USDC on Base, no account or API key needed, returns compact JSON with specific fields, allows tuning with parameters, and treats zero results as a valid response. This goes beyond basic function to inform agent decision-making, though rate limits or error behaviors are not covered.

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 three sentences of efficient information: purpose, output format, tuning, pricing, payment, and edge case. Every sentence earns its place with no redundancy, and key details are 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?

Given the tool's simplicity, high schema coverage, and lack of output schema, the description adequately covers input, output, cost, authentication, and a key edge case (zero results). It could mention error handling for invalid parameters, but overall it provides sufficient context for reliable agent invocation.

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% and each parameter is well-described in the schema (query required, num with default/max/min, country and lang with patterns). The description adds only a summary of the tuning capabilities and the 'plain text' nature of query, which does not substantially extend the schema's information. Baseline score of 3 is appropriate.

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 identifies this as a Google News search tool for AI agents, specifies the source (Serper.dev), and distinguishes it from the related /web/search tool. It explicitly states the input (query) and output format (compact JSON with fields like position, title, url, snippet, publish date, source), leaving no ambiguity about the tool's function.

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 implies usage for news retrieval and mentions pricing and zero-result validity, but does not explicitly state when to use this tool versus alternatives like web_search or web_images. No direct when-not-to-use guidance or differentiation from sibling tools is provided, though it is the only news-specific tool in the sibling list.

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