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

Annotations already establish the safe read profile (readOnly, idempotent, non-destructive), so the bar is low. The description adds genuinely useful behavior beyond the schema: assignee/team/contact are null when unset, and timestamps are returned as unix seconds.

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?

A single front-loaded sentence with no filler, and the lookup key comes first. The long field enumeration is dense but every element earns its place by documenting the return shape.

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, the description carries the burden of describing return values and does so thoroughly: field list, null semantics for unset relations, and timestamp units. An agent has enough to call and interpret it correctly.

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 100%, so the baseline is 3. The phrase 'by its number' aligns with and reinforces the schema's conversation_id description but adds little new meaning, and the fields parameter is not elaborated in prose.

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?

States a specific verb+resource ('Get one conversation') and scopes it to a single record looked up by number, which implicitly contrasts with the list/filter siblings. It doesn't name a sibling explicitly, so it falls just short of the top score.

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?

Usage is only implied: an agent can infer this fetches a specific conversation, but there is no explicit when-to-use guidance or routing against conversation_list, conversation_filter, or list_conversation_messages. Adequate but with clear gaps.

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