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

With no annotations, the description carries the burden of behavioral disclosure. It explains output format (sections array, infobox facts), states there's no HTML/wikitext to parse, and warns that long articles can flood context. It doesn't cover error cases or permissions, but for a read tool the key behaviors are disclosed.

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 concise, front-loaded with the core purpose, and every clause adds meaningful detail. It avoids redundancy with the schema and is well-structured with clear separation between purpose and usage tips.

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?

No output schema exists, so the description compensates by specifying return structure (sections array, infobox facts, no markup). It also covers the main usage concern (context size) and references the sibling lookup. It omits minor details like error behavior, but overall it's sufficient for a straightforward article-fetching tool.

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?

Since schema coverage is 100%, the baseline is 3. The description adds value by explaining why `sections` and `max_chars` exist (to limit context flooding) and how to use them ("pull only the parts you need"), which is beyond what the schema states about their types and defaults.

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 clearly states the tool returns "The full text of an article" and distinguishes it from lookup()'s summary by emphasizing sections as a JSON array and infobox as key/value facts. It also explicitly contrasts with the sibling lookup tool, making its unique role evident.

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 explicitly says to use this tool "when lookup()'s summary is not enough," giving a direct when-to-use vs alternative. It also provides guidance on using `sections` and `max_chars` to avoid flooding context, which is actionable usage direction.

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