mem_suggest_topic_key

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the useful behavioral trait 'stable', indicating deterministic output across calls. However, it does not explain how the key is generated or how edge cases (e.g., empty title and content) are handled.

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, front-loaded sentence with no redundancy. It immediately communicates the tool's purpose and key distinguishing trait ('stable'), making it highly efficient.

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 low complexity, comprehensive parameter descriptions in the schema, and presence of an output schema, the short description is largely sufficient. It lacks only an explicit tie-in to the upsert workflow (e.g., suggesting use before mem_save/mem_update), but this is a minor gap.

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 descriptions cover 100% of the three parameters, including the type enum and title/content fallback behavior. The description itself adds no additional parameter-specific semantics beyond what the schema already provides, so baseline 3 applies.

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 states a specific verb 'suggest' and resource 'stable topic_key' with the context 'for observation upserts'. This clearly distinguishes it from sibling tools like mem_save or mem_get_observation, which perform different actions.

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 phrase 'for observation upserts' implies when this tool should be used, but there is no explicit guidance on when not to use it or how it compares to alternatives. The usage context is clear but not elaborated with exclusions or preferred workflow placement.

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