ragbrain_search

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

With no annotations, the description must fully disclose behavioral traits. It clarifies the tool performs semantic search and returns text chunks, but omits details like read-only nature, authentication requirements, or output format. This is adequate for a simple search tool but lacks depth.

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 concise at two sentences, with no wasted words. It is front-loaded with the core action and result, making it easy to scan.

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 no output schema, the description could better explain return structure (e.g., chunk content, metadata). It covers the basics but lacks details on pagination or result formatting, making it sufficient but not comprehensive.

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 baseline is 3. The description does not add new meaning to parameters beyond the schema; it repeats 'query' and implies results but offers no additional semantic value for parameter usage.

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 performs semantic search across the RAGBrain knowledge base, returning relevant text chunks. This distinguishes it from sibling tools like ragbrain_browse_namespace (navigation) or ragbrain_get_document (retrieval by ID), making its purpose specific and unambiguous.

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 says 'Use this to find information on any topic stored in RAGBrain,' providing a clear general context. However, it does not explicitly mention when not to use this tool (e.g., for precise document retrieval via ragbrain_get_document) or suggest alternatives, leaving room for ambiguity.

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