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

Annotations declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, covering safety and repeatability. The description adds behavioral context by stating the tool is 'schema-aware' and produces 'ready-to-run SQL', implying it reads schema information and returns SQL rather than executing it. This goes beyond the annotations by clarifying the read-only, suggestion-generating nature.

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, front-loaded with the core action and outcome. It contains no redundant phrases and each sentence adds value: the first states what it does, the second indicates when it's most useful. This is a model of concise, well-structured tool documentation.

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?

The tool has an output schema (not shown) and rich parameter descriptions, so return format and parameter semantics are covered. The description clearly explains purpose and use cases, and annotations handle safety. It does not explicitly discuss output quantity or limitations, but the output schema compensates for any return-value details. Overall, the definition is complete for an agent to select and invoke it correctly.

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 100%, with both parameters having detailed descriptions, especially 'connection' which instructs to call list_connections and resolve names semantically. The tool description itself does not add parameter-specific meaning beyond high-level phrasing like 'schema-aware'. Since the schema already carries the full param burden, the baseline of 3 is appropriate.

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 'generate' and resource 'schema-aware query suggestions' with a clear deliverable ('ready-to-run SQL'). It distinguishes this from siblings like query_sql (executes) or explain_query (explains) by focusing on suggestion generation. The stated use cases ('exploring unfamiliar databases or finding useful queries') reinforce its unique role.

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 explicitly states when to use the tool: 'Great for exploring unfamiliar databases or finding useful queries.' This gives clear contextual guidance, though it does not mention alternatives or exclusions. The guidance is clear enough for an agent to select it appropriately among siblings.

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