Get conversation history

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It signals a read operation by saying 'Returns', but it omits key behavioral traits such as ordering, pagination, whether recalled or system events are included, and how the optional limit affects results.

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?

One sentence, front-loaded with the operation and resource, with no filler or repeated schema information. Every word contributes to defining the output.

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?

With no output schema and no annotations, the description is the only source of return semantics, yet it omits important context such as the effect of limit, ordering, and possible event types. It is adequate enough to guess the main purpose, but not complete enough to call reliably in all cases.

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 input schema has 0% description coverage, yet the tool description still does not explain conversationUrn or limit. The word 'conversation' is a weak allusion to conversationUrn, but no format, example, or additional semantics are provided beyond what the schema already shows.

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 clear verb ('Returns') and names the resource ('conversation') and the output shape ('events with id, sender, text, sent time'). It does not explicitly differentiate from siblings like get_conversations, but the event-level focus makes the intended purpose recognizable.

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?

No guidance is given on when to choose this over get_conversations, send_message, or other conversation-related siblings. The description states what the tool returns but never says when to use it or which alternatives it should replace.

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