livescience_headlines

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

No annotations are provided, so the description carries the behavioral disclosure burden. It does indicate this is a read-style operation returning 'fresh' headlines from a 'public section hub page,' which signals a public, non-destructive source. It does not mention output format, pagination, rate limits, or failure behavior, though those are less critical for a simple public headlines fetch.

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 two short sentences with no filler. The opening verb phrase is front-loaded, and phrases like 'fresh' and 'public section hub page' add useful behavioral context without redundancy.

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 one-parameter tool with a fully enumerated schema and no output schema, the description provides enough for an agent to know what input to supply and what to expect at a high level. The only mild gap is that it doesn't describe the shape or fields of the returned headlines, but 'Returns ... headlines' is arguably sufficient for this simple use case.

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 schema covers 100% of the single parameter and already documents the required 'section' enum with 'Live Science section slug.' The description only echoes 'section headlines' and adds no additional parameter-level meaning, so it does not go beyond 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 identifies the verb ('Get'), resource ('Live Science section headlines'), and source ('one public section hub page'), so the tool's purpose is immediately understandable. It doesn't explicitly distinguish this from sibling tools like livescience_news or livescience_article, but the 'section headlines' scope is specific enough.

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 implies the intended use case: obtain headlines for a given Live Science section. However, it gives no explicit guidance about when to prefer this tool over siblings such as livescience_news, livescience_sections, or livescience_article, and it names no alternatives or exclusions.

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