get_events

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

No annotations are provided, so the description carries the burden. It implies read-only behavior through the verb 'Read' and 'query', but does not disclose details like default pagination, ordering, or side effects. This is adequate but not rich.

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?

Two sentences with no redundancy. The first states the core function, the second gives actionable examples. Every word 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?

Given the schema covers all parameters and an output schema exists, the description is sufficient in conveying purpose and usage context. It could mention default behavior when no filters are applied, but this is a minor gap.

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%, which sets a baseline of 3. The description adds value by showing how filters combine in real scenarios (e.g., 'all upcoming conferences' maps to upcoming_only and event_type, 'draft status' maps to status), going beyond the isolated schema descriptions.

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 the tool reads structured events from the Events collection with filtering capabilities. It provides concrete examples (upcoming conferences, draft status) that make the purpose immediately understandable and distinguish it from write/update tools.

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?

Explicitly recommends use for querying pipeline-harvested events and gives two practical use cases. However, it does not mention any alternatives or exclusions (e.g., when to use get_events_overview instead), so it misses the full criteria for a 5.

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