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

Annotations already declare the operation read-only, idempotent, and non-destructive. The description adds meaningful behavioral details beyond that: the default and maximum row limits (25/100) and the unusual slug behavior that returns sponsors from comparable events not sponsoring this one. This helps the agent understand what the tool actually returns and how it behaves at boundaries.

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 short sentences with no filler. It front-loads the core purpose, then lists filters, limits, and the special slug behavior in natural order. Every sentence earns its place.

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?

For a read-only, filterable list tool with 5 optional parameters and no required fields, the description gives enough information to invoke it correctly. It covers what is returned, how to filter, the limit behavior, and the optional enrichment via slug. The lack of an output schema is acceptable because this is a list-retrieval tool and the descriptions focus on selection semantics.

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 the input schema already describes each parameter and the default/maximum limit. The description reinforces the same information ('Filter by city, country or topic', 'Up to 25 by default, 100 at most') without adding meaningfully new semantics. This meets the baseline for a fully covered schema.

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 identifies the resource: upcoming conferences with a sponsor page or prospectus, and the intended use case for marketers seeking sponsorship opportunities. It is immediately distinguishable from sibling tools like search_conferences or get_conference by focusing specifically on conferences 'open for sponsorship'. The phrasing 'see who is taking sponsors now' adds a concrete, actionable purpose.

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 gives clear context for when to use the tool: when a marketer wants to find conferences currently accepting sponsors. It also explains the available filtering dimensions (city, country, topic) and the optional slug behavior. However, it does not explicitly say when NOT to use this tool or compare it to alternatives.

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