list_tickets

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

No annotations are provided, so the description must cover behavior. It mentions pagination (offset/limit defaults and max) and filter logic, but does not disclose the return format, potential errors (e.g., missing filter), authentication needs, or rate limits. It is adequate but lacks full behavioral disclosure.

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 longer than average but well-structured with a table and clear sections. It frontloads the main purpose and then provides detailed heuristics. Every sentence adds value, though some repetition exists between schema descriptions and the heuristic. Overall, it is concise relative to the complexity.

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?

Given 15 parameters and no output schema, the description covers filter logic thoroughly but misses the return value format and any constraints like the required filter (schema says required is empty, but description states 'at least one filter required' – a minor contradiction). It also doesn't mention when to use list_tickets vs get_ticket. The heuristic is strong, but completeness is not fully achieved.

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?

Despite 100% schema coverage, the description adds significant value beyond the schema with a heuristic table, examples (e.g., 'cansados' for desk_name), and resolution strategies (using search_user for IDs). It transforms parameter understanding into a decision tree for user intents, making it highly semantic.

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 lists tickets from TiFlux with filters, using a specific verb and resource. It distinguishes itself from create, get, and close siblings by focusing on listing. However, it doesn't explicitly differentiate from other list tools like list_appointments, though the name and context make it clear.

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 explicit when-to-use guidance, including a heuristic table mapping user input types to the correct filters (e.g., desk_name vs client_name vs requestor_email). It also advises when not to use certain parameters and how to resolve IDs via search_user, offering comprehensive decision context.

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