section_text

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

With no annotations provided, the description must carry the behavioral burden. It does this well by disclosing the read-only parse API, redirect-following, close-match suggestions for misspelled headings, return structure ('clean text with paragraph structure'), and the deep-link at the bottom. It does not mention error cases or rate limits, but the disclosed behaviors go well beyond a minimal description.

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 dense but well-organized, front-loading the core purpose and then explaining arguments, output, and redirect behavior. Every sentence contributes useful information, though the deep-link sentence is slightly peripheral and could be considered extra detail.

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?

Given no output schema and no annotations, the description covers what the tool returns (clean text with paragraph structure), how to identify a section, what happens with misspellings, how redirects are handled, and when this tool beats its siblings. An agent has enough to select and call the tool correctly.

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?

The input schema already documents all parameters with descriptions, giving 100% coverageوط; however, the description adds valuable semantics beyond the schema: section numbers are exactly as shown by `article_sections`, 0 reads the lead/intro, headings are case-insensitive, and misspelled headings get close-match suggestions. This meaningfully helps an agent construct correct arguments.

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 opens with a specific verb and resource: 'Read ONE section of a Wikipedia article as plain text'. It distinguishes itself from siblings by naming `article_sections` and `article_extract`, making its scope immediately clear.

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 description explicitly says when to use this tool instead of `article_extract` ('no need to pull the whole 50KB+ article') and positions it as the targeted-reading companion to `article_sections`. It also gives concrete argument-passing guidance, so an agent knows exactly how to invoke it.

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