knowledge_base_info

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

No annotations are provided, so the description carries the disclosure burden. It signals a read-style metadata call and what is returned, but says nothing about permissions, behavior on an empty/uninitialized knowledge base, or whether the call has any cost or side effects.

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?

Two short sentences, front-loaded with the return payload and followed by the motivating use case. Nothing is padded, though the value could have been sharpened slightly by naming the sibling it contrasts with.

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?

An output schema exists, so return values need not be described, and with zero parameters there is no schema gap to compensate for. The only missing element is any note on failure/empty-state behavior in the absence of annotations.

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 tool takes zero parameters, so there is nothing for the description to clarify; the baseline for a parameterless tool applies. The description adds no spurious parameter-like claims.

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?

Uses a specific verb (returns) with a specific resource (knowledge base) and enumerates the returned metadata: total chunks, unique sources, collection name, embedding model. This clearly separates it from the search-oriented sibling knowledge_search, though it never names that sibling explicitly.

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?

Gives an explicit purpose context: verifying that PDF ingestion completed successfully. It does not state when not to use it or point to an alternative, so it falls short of full when/when-not guidance.

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