wiki_attention

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

With no annotations, the description carries the full burden and does well: it discloses a dedicated rate lane ('Own rate lane'), a 24-hour cache, and the branching failure mode (has_article=false with a related_article suggestion). It does not mention auth requirements or pagination, so it falls short of a perfect 5.

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 core question is front-loaded in the first sentence, followed by output shape and constraints. It is dense and slightly cramped, but every sentence carries information; no 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?

For a 3-param tool with an output schema, the description is complete: it covers inputs, return shape, fallback behavior, caching, and rate-lane characteristics. An agent has everything needed to call it and interpret results despite zero schema description coverage.

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 0%, so the description must compensate, and it does: it documents the `days` range (7-90), `lang` as the Wikipedia edition with examples ('en', 'pt', 'de'), and `topic` implicitly via the exact-title lookup. It omits the default value for `days`/`lang` but adds real meaning beyond the bare schema.

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: it answers whether Wikipedia has an exact-title article for a topic and whether attention is growing. The output contract (exact article fields, daily pageviews, has_article=false fallback) is spelled out, so an agent can distinguish it from siblings like interest_over_time or news_coverage.

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 hints at usage ('verify gaps before citing') and describes what happens when no exact article exists, which implies a validation use case. However, it never explicitly contrasts itself with any sibling (e.g., interest_over_time for Google Trends vs. this for Wikipedia), leaving the when-to-choose decision to inference.

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