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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds real value beyond them by disclosing the negative return scope ('no message text or customer details'), which prevents the agent from expecting conversation content, plus the found/not-found outcome.

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?

Three short sentences ordered as trigger, return shape, exclusion – front-loaded and free of filler. The final exclusion is terse enough to be slightly ambiguous about what 'chat' means here, but it still earns its place.

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 an output schema present, return values need not be enumerated, and the description covers trigger, outcome, and what is deliberately omitted. The remaining gap is sibling routing – it never says when to prefer get_conversation over this UI-context tool.

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?

There is a single parameter with 100% schema description coverage, so the schema already defines conversationId. The description adds no syntax, format, or sourcing detail beyond 'the user selected', so baseline 3 applies.

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 and resource ('opens a conversation the user selected') and scopes it to the embedded Supovia inbox view, so the agent knows it is an inbox-driven open, not a generic fetch. It does not name or contrast the closest sibling, get_conversation, so differentiation is left partly to inference.

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 trigger condition is explicit ('Use this when the embedded Supovia inbox opens a conversation the user selected') and there is one exclusion ('Not for questions asked in chat'). It stops short of routing the agent to an alternative such as get_conversation when full message content is needed, which is the obvious adjacent case.

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