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

Annotations already declare readOnly, idempotent and open-world behavior, so the description's added value is the disclosed return shape: each match carries a numeric id, event/venue counts and country. That is real context beyond the annotations, though it says nothing about no-match results or ordering.

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, front-loaded with the lookup action, followed immediately by the return contents and the downstream use. No filler or restated tool name.

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 two-parameter read tool with no output schema, the description adequately covers purpose, return fields and downstream consumption. What's missing is minor: behavior on zero matches and any result ordering.

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 baseline is 3; the description earns a bump by explaining the purpose of the returned id as the area_id input to ra_event_listings. It doesn't add anything about the limit parameter, which the schema already handles.

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?

States a specific verb and resource ('Look up Resident Advisor area ids') plus concrete examples of the query space (city/region/country names). It also names the sibling it feeds (ra_event_listings), so an agent can place it in the workflow without opening a schema.

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 chaining guidance ('the id is what ra_event_listings needs for its area_id argument') tells the agent exactly when this tool is the right call. It stops short of naming when-not conditions or distinguishing from ra_artist/ra_venue, which remain only implicitly different.

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