mnemostack_answer

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

With no annotations, the description provides moderate transparency: it mentions hybrid recall and LLM inference, and returns confidence and fallback_recommended. It does not disclose potential side effects or resource usage beyond recalling memories, and no annotation contradictions are present.

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 highly concise: two sentences plus a structured return list. Every part adds value, no fluff or redundant information.

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 presence of an output schema (context signal), the return list is helpful but not required. The description misses details on parameter effects (e.g., how limit affects recall), edge cases (e.g., empty memory), and fallback behavior. It is adequate but not comprehensive.

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 coverage is 0%, but the description does not explain the 'query' or 'limit' parameters beyond the tool's purpose. The return list hints at output but adds no semantic guidance for input parameters, leaving agents with only the schema defaults.

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 'Generate concise factual answer from retrieved memories,' specifying the verb (generate) and resource (answer from memories). It distinguishes from siblings like mnemostack_search, but doesn't explicitly differentiate, leaving some ambiguity.

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 implies this tool is for synthesizing answers from retrieved memories, in contrast to search which retrieves raw memories. However, it lacks explicit guidance on when to use this vs alternatives, such as when a direct answer is needed versus when further search is required.

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