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 add useful concrete traits: output shape (JSON rows or CSV) and a per-call price ($0.003). It omits any behavior around malformed HTML, multiple tables, or failure modes, but for a simple extraction tool the basics are present.

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 a single efficient sentence with no filler; the core action is front-loaded. It earns a four rather than five because it is so terse that some needed context is missing, but conciseness itself is handled well.

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?

Given a large sibling set and a closely related ddg_html_to_structured tool, this one-liner does not provide enough context about HTML source requirements, table-selection behavior, or when this tool should be preferred. The output schema exists and reduces the need to explain return values, but the absence of usage and limitation context leaves a clear gap.

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 coverage is 0%, so the description must explain the parameters. It indirectly documents the output side of the 'format' parameter by mentioning JSON and CSV, but it does not explain the expected 'html' input beyond the obvious, and 'agent_id' is entirely unexplained. This is insufficient compensation for a three-parameter schema.

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 verb and resource ('Extract HTML tables') and states the output forms (JSON rows or CSV), so an agent can tell what the tool does. It does not distinguish itself from the closely named sibling ddg_html_to_structured, so it misses the top score.

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 phrase 'Extract HTML tables as JSON rows or CSV' implies the main use case: the agent should invoke this when HTML contains tables to be converted. However, it gives no explicit alternatives, exclusions, or conditions, and the sibling ddg_html_to_structured could plausibly overlap in purpose.

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