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

With no annotations, the description carries the full burden, and it does disclose two important traits: the tool is paid and it shares the same price and payment flow as run_query. That is real value beyond structured fields, but it omits failure modes, whether non-HTML responses are handled, and what the paymentHeader/agentId parameters actually require.

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?

A single front-loaded sentence with no filler: what it does, what it returns, and its pricing relationship to run_query. Every clause earns its place.

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 annotations and no output schema, the description must cover a lot, and it does explain the return content and the paid nature. Gaps remain around error behavior and the undocumented agentId/paymentHeader inputs, which an agent would need before invoking it successfully.

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 only 33% — only url is documented; agentId and paymentHeader have no schema descriptions. The description mentions payment flow but never explains these two parameters or how the payment header is supplied, so it fails to compensate for the coverage 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?

States a specific verb and resource: fetches a URL and returns all meta tags (Open Graph, Twitter Card, standard) plus response headers, and frames itself as a wrapper over run_query with mode="metadata". That is clear and actionable, but it never distinguishes itself from the sibling call_meta_tag_checker, which appears to cover adjacent ground.

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?

"Convenience wrapper around run_query with mode="metadata"" implicitly tells the agent to prefer this over hand-building the equivalent run_query call, which is genuine usage guidance. However, there is no explicit when-to-use/when-not and no comparison against call_meta_tag_checker or the other extraction siblings, leaving the choice to inference.

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