Get website traffic stats

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is covered. The description adds useful behavior beyond annotations: it discloses that bounce rate and avg duration are derived from raw counts, that compare defaults to true, that all-zero results usually mean the range predates tracking, and that a 404 is returned for a bad website ID. It could go further on pagination/timezone details, but this is solid.

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 organized into clear sections (summary, args, returns, examples, error handling) and is front-loaded with the key differentiator. It is somewhat long relative to the schema's completeness, but every section earns its place by adding behavioral or selection guidance rather than repeating schema text verbatim.

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 an 8-parameter tool with 100% schema coverage and no output schema, the description goes well beyond the minimum: it documents the return JSON shape, gives realistic examples, explains defaults, and covers error behavior. A fully complete definition might also enumerate sibling alternatives or disclose timezone defaults, but the gaps are minor given the rich schema.

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 meaningful semantics beyond the schema: it explains the meaning of 'range' values ('Relative... named... or use start_date/end_date'), clarifies the relationship between start_date/end_date and range (overriding), gives the default for compare and response_format, and provides a concrete filters example not fully enumerated in the schema's prose. The Args list is a useful summary even though it mirrors the schema closely.

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+resource ('Get summary traffic statistics for a website over a date range') and immediately distinguishes itself as the 'headline-numbers tool' with pageviews, visitors, visits, bounce rate, and average visit duration. It is clearly differentiated from sibling analytics tools like umami_get_pageviews_series, umami_get_metrics, and umami_get_active_visitors.

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?

Provides clear context on when to use the tool via the 'headline-numbers' framing, examples, and error-handling notes that point to umami_get_website for data-range concerns. It does not explicitly state when NOT to use this tool or list alternatives by name, so it loses a point, but the examples and scope are strong enough for an agent to select it correctly.

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