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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the function without revealing input requirements, dialects supported, output format, or side effects. This leaves the agent without important context about what happens when the tool is invoked.

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 sentence that front-loads the core purpose with no wasted words. Every phrase contributes to understanding the tool's basic function.

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 no output schema and no annotations, the description is too sparse. It omits the expected return value (SQL text), how dialect selection works, and the relationship between the overlapping 'desc' and 'description' parameters. Given sibling tools with similar names, more context is needed to avoid misselection.

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 100%, so based on the rubric the baseline is 3. However, the schema descriptions ('Desc to process') are tautological and the tool description does not clarify the difference between 'desc' and 'description' or acceptable values for 'dialect'. The tool description adds no parameter-level meaning beyond the 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?

States a specific verb and resource: 'Generate SQL from natural language'. This distinguishes it from sibling SQL tools like sql-validate and sql-format, which do not generate SQL. The 'AI' prefix is redundant but does not obscure the purpose.

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?

No explicit guidance on when to use this tool versus alternatives. The description implies the use case (when natural language SQL generation is needed), but it does not mention sibling tools like x402-sql-validate or x402-sql-explain or advise against them.

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