remember

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

Since no annotations are provided, the description carries the full burden. It discloses automatic linking of supersedes/because and mentions the return format, which goes beyond just the function name. However, it does not describe idempotency or side effects beyond linking.

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 moderately concise, with a clear structure separating purpose, parameter details, and return format. A few sentences could be more tightly integrated, but overall it is well-organized.

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 tool has 3 parameters, no output schema (but description includes return format), and sibling tools listed, the description provides enough detail for correct use. Minor improvement would be to explicitly compare with sibling tools.

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 0%, so the description must compensate. It fully explains each parameter: session_text as raw text, date as 'YYYY-MM-DD' with default today, and title as a human-readable source citation. This adds significant meaning beyond the schema.

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 verb 'extract' and the resource 'durable memories', and adds specificity about automatic linking when a decision is overridden. It distinguishes from sibling tools (list_memories, recall) by focusing on memory ingestion.

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 when to use (to extract memories from conversation text) but does not explicitly state when not to use or compare with alternatives like list_memories or recall.

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