remember_turn

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

The description discloses key behavior (splitting into sentences, storing with automatic cues) which is valuable given no annotations. However, it doesn't explain what 'automatic cues' entail or any side effects, leaving some transparency gaps.

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 concise sentences front-load the purpose and usage. Every word adds value with no redundancy or filler.

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?

The description covers the core functionality and usage, but given no output schema and no explanation of max_segments or return values, it is only minimally complete for a tool of this complexity.

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 text parameter is implied through 'splits the text into sentences,' but max_segments is completely unexplained. With 0% schema description coverage, the description fails to fully compensate, leaving one of two parameters ambiguous.

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 the tool saves one conversation turn, splitting text into sentences and storing them with automatic cues. This distinguishes it from the sibling 'remember' by emphasizing turn-level granularity and automatic processing.

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?

It explicitly instructs to call after every user/assistant exchange to keep memory automatic. While this provides clear usage context, it does not mention alternatives or exclusions, so it stops short of a 5.

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