query

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool 'Returns relevant context chunks from the indexed content,' which informs the agent of the return behavior. However, it does not mention potential limitations, error handling, or whether the operation is strictly read-only. For a simple query tool this is adequate but not richly transparent.

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 two sentences long and every word earns its place. It front-loads the core action and resource, then immediately states the return value. There is no redundant information or filler.

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 a single parameter and no output schema, the description covers the essential aspects: what it does, what input it takes, and what it returns. It lacks detail on response size or potential pagination, but given the simplicity of the tool, the description is reasonably 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?

The schema already provides a clear description for the 'question' parameter ('The question to search for in the knowledge base'). The tool description adds the nuance that this is a 'natural language question,' clarifying that the agent can formulate queries in everyday language rather than requiring specific keywords. This adds meaning beyond the schema description.

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 function: 'Query the Knowledge Base knowledge base with a natural language question.' It specifies the verb (Query), the resource (Knowledge Base), and the expected output (relevant context chunks). This differentiates it from the sibling tool 'list_sources' which lists sources rather than performing semantic queries.

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 context for when to use the tool: when you have a natural language question about the knowledge base. It does not explicitly mention alternatives or when not to use it, but the use case is evident from the phrasing. For a single-purpose query tool with a sibling that lists sources, this level of guidance is sufficient.

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