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

No annotations are supplied, so the description carries the burden of explaining behavior. It does say that markup is discarded, but it does not disclose whether a network fetch occurs, whether the tool is read-only, what it does with the many optional parameters, or what error conditions apply.

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 short and front-loaded with the core topic and output behavior. It is not padded, though the brevity contributes to under-specification rather than clarity.

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 nine optional parameters, no output schema, and no annotations, the description is insufficient. It does not say which parameter supplies the source content, whether a required URL is expected, or what the return value actually looks like beyond '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?

Schema description coverage is 100%, which sets the baseline at 3. The description adds no parameter-level guidance, and the schema's generic parameter descriptions do not clearly connect the parameters to Open Graph counting, but the high schema coverage prevents a lower score.

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 identifies the broad purpose — returning an Open Graph tag count and discarding markup — so an agent can tell this is about OG tags rather than URL normalization or fetching. However, it is a noun phrase rather than a clear verb-and-resource statement, and it does not specify the input source that the tags are counted from.

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?

There is no explicit when-to-use guidance. 'Markup discarded' weakly implies this tool is for counting rather than retrieving markup, but it does not mention alternatives, prerequisites, or when not to call this tool over siblings like web-fetch or normalize-url.

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