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

Goes well beyond the annotations (idempotentHint, destructiveHint): it explains that urgent true/false map to dashboard actions, both clear needs_attention, resolving resets an unhappy sentiment to neutral, the AI re-reads urgent/needs_attention on each reply so marks expire, is_read never sends a read receipt, and a no-change write is a no-op. This is rich, non-obvious behavioral disclosure consistent with the annotations.

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?

Front-loaded with the one-line purpose followed by dense but each-sentence-earns-its-place detail. It is on the longer side but the length is justified by the interaction complexity between urgent, needs_attention, sentiment, and ai_enabled.

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 6-parameter mutation tool with no output schema, the description covers the write semantics, side effects, and the sibling alternative thoroughly. The only gap is that it does not describe the response shape, though annotations and schema carry most of the remaining load.

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 coverage is high (83%), so the baseline is 3, but the description adds meaning beyond the schema by tying urgent/sentiment/needs_attention interactions together and clarifying AI-read timing for ai_enabled. The status enum meaning is left to the schema, which is fine at this coverage level.

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 (change) and resource (a conversation's state) and enumerates exactly which fields are affected: status, read for the team, urgent, and the AI switch. It even names the sibling resumeConversationAi as the alternative for one case, so an agent can distinguish it from related tools without opening the schema.

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?

Gives a clear routing rule: a pause started by a teammate's reply is ended with resumeConversationAi instead of ai_enabled:false. That is explicit context for choosing between alternatives, but there is no general statement of when to reach for this tool versus, say, assign_conversation or update_contact.

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