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

Beyond the annotations (which already declare read-only, idempotent, non-destructive), the description discloses the concrete sampling window (50 most recently active conversations), the display cap (up to 20), the returned fields, and what is deliberately omitted (no message text or customer details). This is meaningful behavioral context an agent cannot get from the schema or 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?

Two sentences, front-loaded with the usage condition, followed by the precise return semantics. No filler or restatement of the title.

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 zero-parameter read tool with annotations and an output schema, the definition covers everything needed: when to call it, what it returns, its caps, and what it excludes. No gaps remain that would cause a misselection or misuse.

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 tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly adds no parameter content and instead clarifies the implicit scope of the query.

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 ('see their unread customer conversations in an inbox view') and scopes it precisely to unread items in an inbox view. This clearly separates it from siblings like list_conversations and get_unresolved_conversation_counts, which the agent could otherwise confuse it with.

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?

Opens with an explicit usage trigger ('Use this when someone wants to see their unread customer conversations') and adds an exclusion ('Not for complete open-conversation totals'). It stops short of naming the alternative tool for that excluded case, so the routing cue is present but not fully explicit.

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