memory_labels

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

The description discloses the output format ('Returns {kinds, topics}') and implies a read-only operation via 'List'. With no annotations provided, the description carries the full burden, and it does so adequately for a simple list tool. However, it could explicitly state that no changes are made.

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: the first clearly states the action and output, the second gives usage guidance. No redundant information, every sentence serves a purpose.

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 simplicity of the tool (no parameters, no output schema, no annotations), the description is fairly complete. It covers the purpose, output, and usage context. It does not explain what 'kinds' and 'topics' mean, but that is likely domain knowledge.

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 input schema has no parameters, so schema coverage is 100%. The description adds value by explaining the output structure, but parameter semantics are not applicable. Since there are no parameters, the description cannot add meaning beyond the schema, but it still provides useful 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 explicitly states the action ('List the schema of active memory labels') and the scope ('in the current default repo'), and specifies the return structure ('Returns {kinds, topics}'). It clearly differentiates from sibling tools like memory_list or memory_get by focusing on label schemas rather than memory entries.

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 guidance on when to use the tool: 'Use this before inventing a new kind or topic, to reuse existing labels.' It does not explicitly state when not to use it, but the use case is well-defined. No alternative tools are needed as no sibling tool provides the same functionality.

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