kivest_search

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

With no annotations, the description carries the full burden of disclosing behavior. It adds useful details about rate limiting, automatic queuing, and model-specific RPMs. But it does not explicitly state that the tool is read-only, nor does it describe the response format or error behavior. This is acceptable but not comprehensive.

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 organized into a short intro, a model breakdown, and a 'Best for' note. Every sentence provides useful information without redundancy. It is slightly longer than necessary but still tightly structured and front-loaded with the core purpose.

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?

For a tool with 4 parameters, no annotations, and no output schema, the description covers the essential aspects: purpose, model selection, rate limits, retry behavior, and ideal use cases. It does not describe the response format, but that is not mandated in the absence of an output schema. It provides enough context to invoke the tool correctly, though additional detail on return values would make it more 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 description coverage is 100%, so the baseline is 3. The description adds meaningful semantics for the 'model' parameter by explaining each model's characteristics (e.g., 'Fast, high-quality results', 'Unlimited requests, open source'). This goes beyond the enum values. Other parameters (query, maxTokens, temperature) are adequately described in the schema, and the description doesn't need to add more.

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's purpose: 'Search the web using Kivest AI Search API.' This is a specific verb+resource that identifies the core function. However, it does not differentiate itself from siblings like kivest_web_search or kivest_search_stream, so it falls short of a 5.

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 clear usage context with 'Best for: Current events, factual queries, general knowledge.' It also notes rate limits and model-specific limits, which helps an agent decide when to call it. However, it does not explicitly contrast with alternative search tools like kivest_web_search or kivest_image_search, so it lacks explicit when-not-to-use guidance.

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