read_conversation

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

With no annotations provided, the description carries the full burden. It discloses that messages are returned newest first, that reading does not mark as read, and explains the unread counter behavior. It does not mention authentication requirements or rate limits, but the core read behavior is transparent. The presence of an output schema compensates for the lack of return format details.

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 brief and well-structured: a clear purpose statement, usage examples, a prerequisite link, a behavioral note, and parameter definitions. Every sentence adds value, and there is no redundancy or fluff.

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?

For a simple read operation with two parameters and an output schema, the description covers purpose, usage, parameter semantics, and a key behavioral nuance (unread marking). It does not mention error handling or rate limits, but these are not critical for a straightforward read tool, and the output schema fills the return format gap.

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, but the description adds meaning by explaining that channel_id comes from list_message_targets and that limit controls how many recent messages are returned. This provides essential context beyond the schema's type and default, making the parameters understandable.

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 reads Discuss conversations, gives concrete examples of when to use it (e.g., 'what did they write to me'), and explicitly distinguishes from the sibling tool 'list_message_targets' by explaining that the latter provides the channel_id and unread count. This leaves no ambiguity about the tool's purpose.

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 explains when to use the tool (to answer questions about conversation content) and provides a prerequisite ('list_message_targets gives you the channel_id'). It also notes that reading does not mark as read, which is important for usage context. However, it does not explicitly state when not to use it or compare to alternatives like send_channel_message, though the differentiation is implied.

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