Базы знаний

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

Annotations already declare this a read-only, open-world, idempotent operation. The description adds meaningful behavioral context beyond that: it specifies that without 'base' it returns all knowledge bases with settings, and with 'base' it also returns a material list with parsing status. This gives the agent insight into output richness and conditional behavior, though it does not cover edge cases like empty results or pagination.

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 a single, compact sentence that front-loads the core behavior and then expands on the conditional variant. Every word contributes to understanding the tool's output and parameter effect, with no fluff or redundancy.

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 simple optional-parameter structure, no output schema, and strong annotations, the description adequately explains what the tool returns under both invocation modes. It would benefit from mentioning return format details or pagination, but the provided information is sufficient for an agent to know what to expect in typical use.

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% for both parameters ('base' and 'case'), so the schema already documents their meaning. The description adds conditional behavior tied to 'base', but this is more about output shape than parameter semantics. The 'case' fallback behavior is already documented in the schema, so the description does not significantly elevate parameter understanding.

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 indicates the tool lists knowledge bases ('все базы знаний дела с их настройками') and optionally their materials when 'base' is provided. It distinguishes itself from sibling tools by detailing the conditional output scope, making the purpose specific and non-tautological.

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 by explaining the behavior with and without the 'base' parameter, effectively telling the agent when to expect different result sets. It does not explicitly name alternative tools or exclusions, but the context is sufficient for choosing this tool over knowledge_search or knowledge_save.

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