memory_store

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

Annotations indicate readOnlyHint=false and destructiveHint=false. Description adds context about structuring Japanese context and auto-extracting facts via LLM, which is valuable beyond annotations. It does not contradict annotations, but could clarify overwrite or idempotency behavior.

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 with no extraneous words. It front-loads the primary purpose and then details the key feature (auto_extract), achieving high efficiency.

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 4 params with full schema coverage and no output schema, the description covers the main use case and a key feature. It does not specify whether storage is append-only or updateable, but this is acceptable for the complexity level.

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 100%, so baseline is 3. The description adds minimal parameter-specific info beyond what the schema provides, mentioning that auto_extract triggers LLM fact extraction, but this is already implied in the schema description.

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?

Description explicitly states the tool saves conversation or event episodes to permanent memory, with specific mention of handling Japanese context. This clearly distinguishes it from sibling tools like memory_recall (retrieval) and memory_extract (extraction).

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?

Description clearly indicates when to use the tool: for storing episodes with Japanese context. However, it does not explicitly mention when not to use it or provide direct comparisons with alternative memory tools.

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