web_fetch_section

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

Without annotations, the description carries the full burden. It mentions case-insensitive heading matching, which is useful, but does not disclose whether nested headings are included, what happens if the heading is not found, or the format of returned content.

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 composed of three concise sentences, each serving a clear purpose: stating the action, highlighting case sensitivity, and providing usage guidance. No unnecessary words or repetition.

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 the simplicity of the tool (3 parameters, no output schema), the description adequately covers core behavior and usage. Minor gaps exist, such as behavior when no heading is found or handling of nested headings, but overall it is sufficiently complete for an agent.

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% with parameter descriptions. The description adds value by specifying 'Case-insensitive heading match' for the heading parameter, which is not in the schema. However, it does not add semantics for url or timeout beyond what is in the 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?

The description clearly states it fetches only content under a specific heading, using a case-insensitive match, which distinguishes it from siblings like web_fetch_chunked or web_fetch_code that fetch entire documents or other sections.

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 to use this tool 'when you only need a specific part of a large document,' providing clear usage context. It does not mention when not to use or mention alternatives, but the guidance is sufficient for a focused tool.

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