ticket_stats

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds behavioral value by disclosing which aggregates are returned, but says nothing about the scope of the aggregation (all tickets vs. a subset), whether the counts are cached, or any rate/refresh behavior.

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 short sentence with no wasted words, and the most distinctive metrics are listed first. It is grammatically a fragment with no stated verb, which slightly reduces clarity but not length efficiency.

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, the description need not explain return values, and with zero parameters there are no inputs to document; annotations cover the safety profile. The only residual gap is that the aggregation scope (which tickets are counted) is unstated.

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 the baseline is 4 and there is no parameter semantics for the description to clarify. Nothing here misleads about inputs.

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 enumerates exactly what is computed — counts by status and priority, unassigned work, and oldest open ticket age — which is far more specific than a generic 'ticket statistics' phrasing. It is a noun-phrase fragment with no explicit verb, so the agent must infer 'returns aggregate statistics', but the metric list distinguishes it clearly from siblings like search_tickets and get_ticket.

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?

There is no when-to-use guidance, no statement of what this tool is for in a workflow, and no mention of alternatives (e.g., use search_tickets when you need individual records rather than aggregates). The agent must infer the routing from the metric list alone.

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