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

Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description mentions two modes (top stories vs search results), but does not add detail on pagination, rate limits, or return format, which are beyond the annotations.

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 short sentences: the first states the primary purpose, the second clarifies input flexibility. No redundant content or filler; the key information is front-loaded.

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?

With only one parameter, full schema coverage, and read-only/open-world annotations, the description is adequate for correct invocation. It does not describe the output structure, but the purpose statement ('extract top stories or search results') implies the return type. Slightly more detail on expected output would make it 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?

Input schema fully documents the single 'url' parameter with concrete examples (HN URL, Algolia API URL, plain query). The description repeats this information nearly verbatim, adding no meaningful new semantics beyond the schema's 100% coverage.

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?

Clearly states it extracts top stories or search results from Hacker News, with a specific verb and resource. The tool name and sibling pattern make it stand out among other extract_* tools.

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?

Provides clear context on what the tool does and what inputs it accepts (HN/Algolia URL or plain search query), but does not explicitly list alternatives or exclusions. The sibling names make the intended use obvious, so it meets the 'clear context, no exclusions' bar.

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