pageviews

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

No annotations are provided, so the description carries the burden and does well: it discloses the upstream source (Wikimedia's pageviews REST API), the default window semantics (last 7 days ending yesterday UTC), and the return shape. It omits error behavior, rate limits, and whether the title must match exactly, which mutes a perfect score.

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 sentences, each earning its place: purpose, situational use, source API/default window, and return format in that order. Front-loaded with the core verb and free of filler.

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?

With no output schema, the description correctly compensates by naming the return contents (total, daily average, markdown table). Defaults, source, and return format are all covered for a straightforward read-only lookup, leaving nothing an agent needs missing.

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 itself documents title, start, end, and lang. The description's note about the default window duplicates the schema defaults rather than adding new syntax or format meaning, so the baseline 3 applies.

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 ('Get daily view counts for a Wikipedia article') with scope ('over a date range'), which separates it from the sibling aggregate tools like top_reads and recent_changes. An agent can identify the resource type (per-article pageviews) without opening the 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 parenthetical '(popularity research, trending topics, historical interest)' gives clear situational context for when to reach for this tool. It stops short of naming an alternative or stating when-not to use it (e.g. vs. top_reads for site-wide rankings), so it doesn't reach the top band.

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