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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior. The description adds valuable context by naming the underlying Wikimedia Analytics REST API and explicitly stating that no authentication is required, which goes beyond what the annotations provide.

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?

Three tight sentences: first states the primary operation and scope, second covers the optional filters, third gives data source and auth requirements. No filler or redundant repetition.

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?

The description plus the rich schema and annotations fully cover what an agent needs to call this tool correctly: required params, optional filters, granularity options, source API, and auth status. Output schema exists, so return shape does not need to be described.

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 description coverage is 100%, so the schema fully documents all six parameters. The description adds useful examples for project and restates filter categories, but it does not provide significant new meaning beyond what the input schema already declares.

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 uses a specific verb and resource: 'Get total pageview counts for a Wikimedia project... over a date range, bucketed daily or monthly.' This clearly distinguishes it from sibling tools like per_article or top by emphasizing project-level aggregation over time.

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?

It provides clear context that this tool returns aggregate pageview counts for a project, which implies it is for time-series aggregation rather than per-article or top-page lookups. It does not explicitly name alternatives or exclusion conditions, but the scope is clear enough for correct selection.

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