List Tickets

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is known. The description adds behavioral context by noting the tool returns 'raw ticket data' and uses 'cursor-based pagination,' which helps the agent understand the output and pagination behavior beyond the basic read-only hint. It does not disclose rate limits or error cases, but given the annotation coverage, the added context is sufficient.

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?

The description is three sentences with no filler. It front-loads the endpoint and core purpose, then immediately gives the alternative for intelligent search, followed by a concise list of filters and pagination. Every sentence earns its place, making it both efficient and readable.

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?

Even without an output schema, the description thoroughly conveys the tool's role, capabilities, and relationship to a sibling tool. It mentions the endpoint, pagination, filtering options, and trashed-ticket behavior, which is complete for a list-like operation. The agent can confidently decide when and how to invoke this tool based on the description alone.

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 input schema already provides 100% coverage of all 9 parameters with descriptions, so the description does not need to add new syntax details. It does summarize the key filtering categories (customer, external ID, view, rule, ticket IDs, trashed), which helps the agent quickly grasp capabilities, but this is a recap rather than new semantic meaning. Thus, the schema remains the primary source of parameter detail.

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 returns a paginated list of raw ticket data via a GET request, making the purpose specific and actionable. It also distinguishes itself from the sibling tool gorgias_smart_search by explicitly naming that alternative for intelligent search, which eliminates ambiguity.

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 description provides an explicit when-not-to-use directive: 'For intelligent search with auto-detection of emails, names, views, and keywords, use gorgias_smart_search instead.' This clearly guides the agent away from this tool for intelligent search and implies it is the right choice for raw, filterable ticket lists, covering both selection and exclusion criteria.

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