remember_conversation

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

No annotations are provided, so the description carries the behavioral burden. It discloses the core side effect: reconciling extracted facts into long-term memory and possibly performing ADD, UPDATE, DELETE, or NOOP. However, it does not explain under what conditions each operation occurs, whether changes are reversible, or what response the caller can expect.

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 compact and front-loaded with the primary action and operation modes. The Args block is spare and each line adds meaning beyond the schema, which only provides titles. There is no filler or repetition.

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 tool has only two required string parameters and an output schema, so the description does not need to explain return values. It covers the tool's purpose, its side-effectful operation types, and both arguments. The main gap is the lack of criteria for choosing this tool over sibling memory tools, but overall it is largely complete.

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 Args text is the only documentation for both parameters. The description adds real meaning: 'user_id' is the user's unique identifier, and 'conversation_text' is the transcript or statement to remember. For two simple string parameters, this is sufficient compensation.

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 uses a specific verb and resource: it 'Extracts durable facts from conversation text and reconciles them into long-term memory.' The parenthetical operation list (ADD, UPDATE, DELETE, NOOP) clarifies the tool's scope. It does not explicitly name sibling tools, but its write-oriented behavior distinguishes it from list/recall/forget siblings.

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 the tool should be used when conversation text should be persisted to long-term memory, but it gives no explicit when-to-use guidance, no exclusions, and no mention of alternatives like recall_memories or forget_memory. The agent must infer the boundary between this and sibling tools.

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