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

Discloses that results include live SLA state and total count, adding behavioral context beyond the read-only and idempotent annotations. No contradictions with 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?

Three concise sentences, front-loaded with the main purpose, including examples and a key benefit. No wasted words.

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?

While no output schema, the description adequately covers purpose, usage, and key behaviors (SLA state, total count). Sufficient for selecting and invoking the 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?

Schema coverage is 100%, so baseline is 3. The description adds value with query examples, clarifying the syntax expected for the query parameter.

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 clearly states it searches tickets using Zendesk query syntax, distinguishing it from siblings like list_tickets or get_ticket. It specifies the resource (tickets) and the query mechanism.

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?

Provides examples of valid queries and explains the benefit of total count for queue triage, guiding when to use it. However, it does not explicitly contrast with alternative tools like list_tickets.

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