mem_capture_passive

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

The description adds useful postcondition information beyond the sparse annotations: each Key Learnings item becomes its own memory and is filed under the producing tool. While it does not detail side effects or error cases, it provides meaningful behavioral context that is not derivable from annotations.

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 sentences with no fluff. Every clause contributes meaning: action, source, language scope, and storage behavior. The structure is front-loaded and 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?

For a simple write tool with high schema coverage and an output schema present, the description covers purpose and behavior sufficiently. It lacks explicit alternative guidance or caveats, but these are not critical given the tool's straightforward nature.

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%, so each parameter is already explained. The description does not add extra parameter-level semantics beyond noting the content requirement and language scope, which is partially schema-covered. Baseline 3 is appropriate.

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 specifies a concrete action ('Extract and save') and resource ('Key Learnings items a subagent ended with'), and distinguishes itself from sibling tools by noting the items are 'filed under the tool that produced it' and supported in 'twelve languages'. This goes beyond a generic save tool.

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 usage for subagent outputs with a Key Learnings section, but it does not explicitly state when to use this tool instead of alternatives like mem_save or mem_save_prompt, nor does it mention exclusions or conditions. It is not misleading, just minimally guiding.

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