article_extract

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

With no annotations and no output schema, the description carries the full disclosure burden. It usefully discloses the return format ('plain text (no HTML)') and rough size ('typically several paragraphs'), which is real behavioral value. It does not cover failure behavior for missing titles, disambiguation pages, redirects, or truncation limits, so it is only partially transparent.

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?

Two sentences, zero filler, with the primary purpose and the sibling contrast front-loaded. Every clause earns its place and nothing is repeated from the schema.

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 2-parameter read tool with no annotations or output schema, the description covers purpose, output format, and size — enough to call it correctly. Edge-case behavior (nonexistent titles, disambiguation, language fallback) is unaddressed, which keeps it short of fully complete.

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% — both `lang` (enum plus default) and `title` (with examples) are fully documented in the schema. The description adds nothing parameter-specific beyond what the schema already provides, 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 a Wikipedia article's full plain-text extract by title') and immediately distinguishes itself from the `summary` sibling by contrast in length. An agent can tell exactly what this returns and how it differs from the other extract-like tools without opening a 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?

Explicitly names the alternative ('Complements `summary`: use it when the summary is too brief') and gives the selecting condition. The only omission is a when-not case (e.g. use `summary` when you need one sentence), which is easily inferred and does not undermine the routing.

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