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

Goes well beyond the readOnly/idempotent annotations: it discloses the data lineage (TicketSea analysis of TickPick lowest listed all-in prices), sampling constraints (one marketplace, one listing per day, not live inventory), geographic scope (mostly US events), and an attribution obligation. These are the caveats an agent needs to avoid overclaiming the numbers.

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?

Front-loaded with the usage trigger, then behavior, then the attribution caveat — a sensible order. It is dense and runs long in the middle sentence, but every clause (lineage, cadence, scope, attribution) carries information an agent cannot get from the schema.

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-optional-param read tool with an output schema, annotations, and full schema coverage, nothing needed to call it correctly is missing. The description supplies the interpretive context (non-live data, single-source sampling, required attribution) that structured fields cannot express.

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 adds real value by explaining what each mode returns — with slug, one event's lowest price by day since tracking began; with category, that category's figures. It doesn't state that the two parameters combine or that category is ignored when slug is set, which would have taken it to 5.

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 (returns daily ticket price figures, median get-in price, weekly drops/rises) and names the underlying data source. It is clearly distinguishable from siblings like get_event, get_ticket_links, and search_events, which do retrieval/listing rather than price-trend analysis.

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?

Opens with an explicit 'Use this when the user asks whether tickets are getting cheaper or pricier...' trigger list that covers the realistic intent space. It does not name an alternative tool or state when-not to use it, so it stops short of a full routing rule.

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