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

With no annotations, the description carries the behavioral burden; it discloses that titles are discarded and the result is only a count, which is useful. However, it does not mention that this is a live network fetch, possible failure modes, or that optional arguments appear to be ignored.

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 the action front-loaded and no filler. 'Titles discarded' earns its place by setting output expectations.

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?

The description is too thin given 9 optional parameters, no annotations, and no output schema. It does not explain that no arguments are needed (or that arguments are effectively ignored), nor describe what a successful response contains beyond a count.

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 descriptions cover all 9 parameters, so the baseline is 3; the tool description adds no parameter-level meaning. It does clarify that titles are not part of the count, but this is already echoed in the 'feed' parameter 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 uses a specific action ('Count') and a clear resource ('current Hacker News front-page stories'), and adds a distinguishing output constraint ('Titles discarded') that separates it from generic fetch tools. There is no ambiguity about what the tool does.

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 tool should be used when a count of current HN front-page stories is needed, but it does not state when not to use it or name alternative tools such as web-fetch for retrieving titles. Usage context is present only by inference.

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