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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds useful behavioral context by enumerating the metadata returned (tables, columns, lookback, query tips, examples, user limits), though it remains vague about what 'your own limits' actually entails.

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 front-loaded sentence that states the core purpose first and then enumerates the data domains. The long parenthetical is dense but every listed domain adds useful scope information; it could be marginally more structured but is not bloated.

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 an output schema exists, the description need not detail return values, but it still gives a rich summary of what the output includes. It is complete enough for a zero-parameter metadata tool, though it would be slightly stronger if it explicitly linked itself to run_query usage.

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 tool has zero parameters, so there is no parameter semantics to explain. The baseline score for a no-parameter tool is 4, and the description does not need to compensate for missing schema detail.

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 verb ('Returns') and resource ('SQL tables') and clearly scopes the Hyperliquid data domains covered. It distinguishes itself from sibling query tools by indicating it returns metadata such as columns, history depth, query tips, and examples rather than data rows.

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 this is a discovery/schema-introspection tool useful before writing SQL queries, especially through phrases like 'query tips, worked examples and your own limits.' However, it does not explicitly say when to use this instead of run_query or other sibling tools, nor does it state exclusions or prerequisites.

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