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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that the result is a count and that titles are not returned, but it does not explain network dependency, failure modes, or how the optional input parameters relate to the operation.

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 with no filler. The core purpose is front-loaded in the first sentence, and the second sentence adds a meaningful qualifier about what is excluded from the result.

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 tool with no annotations, no output schema, and nine optional parameters described in confusingly different ways, the description is too sparse. It does not state whether parameters are needed, which one selects or overrides the source, or what the exact return format is.

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 description coverage is 100%, so a baseline of 3 applies. However, the description adds no parameter-level meaning: it does not identify which of the nine optional parameters is relevant, and 'Titles discarded' only repeats part of the feed parameter's schema description.

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 names a specific action and resource: count current Hacker News front-page stories. It also clarifies a key output boundary with 'Titles discarded,' which distinguishes it from tools that would fetch or list story content.

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?

No guidance is given about when to prefer this tool over siblings such as web-fetch, fetch-status, or normalize-url. The purpose implies a live-count use case, but there are no explicit alternatives, exclusions, or context cues.

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