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

The annotations are empty, so the description carries the full burden. It does disclose the core behavior—extraction and reporting—and usefully notes programmatic coverage of three syntaxes. However, it omits edge behaviors such as how invalid HTML/URLs are handled, whether there are auth or quota limits, and what a successful or failed report looks like. Since it describes a read-only validation action, the missing details are moderate rather than severe.

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 sentences with no filler. It front-loads the main action, then adds the report behavior and the programmatic advantage over manual tools. Every clause contributes either to understanding what the tool does or why to invoke it.

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 no output schema and no parameter documentation, the description must supply both input and output semantics. It explains the high-level purpose and some of the report content, but it does not specify the input object's expected keys, the returned result structure, or limitations like supported @types or max HTML size. The missing input encoding alone makes this incomplete for reliable invocation.

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 provides zero description coverage: the only parameter is an `input` object with arbitrary string-keyed properties and an open `additionalProperties`. The description mentions "URL or raw HTML" as sources, which conveys the general intent, but it never specifies how those sources should be encoded inside the `input` object (e.g., `{ "url": ... }` or `{ "html": ... }`). For a tool with 0% schema coverage, this is an important gap.

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 states a specific operation—"Structured data validator”—and the exact resources and outputs: extracting JSON-LD, microdata and RDFa from a URL or raw HTML, then reporting missing Google Rich Results fields per @type. This clearly distinguishes the tool from a generic 'run' action and from the manual reference validators it mentions.

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?

It gives clear context for when to use the tool: programmatic validation of the three structured-data syntaxes, "where the reference validators are manual web tools with no public API." There are no sibling tools to differentiate, so the explicit contrast with the manual alternates is sufficient, though it stops short of stating exclusions or failure-handling conditions.

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