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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'top passages with title, layer, url and a snippet' and that content is public with no tenant data. This provides good behavioral insight, though it could mention if results are ranked or any API-specific behavior.

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 long, front-loading the main action and purpose. Every sentence adds value: what it searches, when to use, and what it returns. No wasted words.

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 and the existence of an output schema, the description adequately covers purpose, usage, and return fields. The only shortfall is the lack of parameter explanations, which reduces completeness slightly.

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 0%, so the description must compensate, but it does not explain any parameter details. The 'query' parameter is implied but not described as a search string, and 'k' (default 5) is not mentioned at all. The user must infer their meaning from context.

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 searches 'agent4.io's own product docs' and distinguishes between 'concepts' and 'cookbook recipes'. This specifies the resource and scope, differentiating it from siblings like 'search_knowledge_base' which searches user knowledge bases.

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 explicitly advises using the tool when unsure about a feature, term, or how to build something. It mentions the content is public and involves no tenant data, providing clear context. However, it does not explicitly state when not to use it or compare directly with alternatives like 'search_knowledge_base'.

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