ticketmaster_suggest

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool returns autocomplete suggestions, indicating a read-only, non-destructive operation, but it omits details about result format, limits, or error behavior. The description is adequate but thin.

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 two concise sentences, front-loaded with the primary verb and resource, and contains no redundant or filler content. Every word contributes to understanding the tool's purpose and behavior.

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?

This is a simple one-parameter tool with no output schema, so the description carries the burden of explaining inputs and outputs. It covers the core behavior (suggestions for partial queries) sufficiently for an autocomplete utility. It could detail the suggestion payload structure, but for a suggest tool this is often unnecessary and the description remains complete enough for basic selection.

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 fully covers the sole parameter q with a description that already states 'Partial artist, event, team, or venue query'. The tool description repeats this information but omits 'teams', adding no new semantic value. With 100% schema coverage, a baseline score of 3 is appropriate.

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 uses the specific verb 'Suggest' and names the resource types (artists, events, venues), clearly distinguishing it from full-search siblings like ticketmaster_search_events. The phrase 'autocomplete suggestions for a partial query' precisely conveys the tool's autocomplete role.

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?

It clearly signals the intended use case: providing autocomplete suggestions as a user types a partial query. While it does not explicitly exclude alternatives or name sibling tools, the partial-query phrasing makes the use case obvious. No misleading guidance is present.

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