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

Annotations already declare readOnlyHint=true, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds the supported dialect range but says nothing about behavior beyond the options, such as how unsupported syntax is handled or error output. Adequate but thin against an already-annotated tool.

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?

Two tight sentences with the primary purpose front-loaded and no filler. It is efficient, though the second sentence reads as option listing rather than routing guidance.

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?

An output schema exists so return values need not be explained, and the description covers the tool's scope and main options. Given the low schema coverage, a bit more detail on the dialect and keywordCase enums would make it fully complete.

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 25% (only 'sql' is documented), so the description must compensate. It partially does by explaining keyword case, indent values (2 or 4 spaces), and dialects, but it omits the full dialect enum, the keywordCase enum values, and defaults, leaving real gaps.

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 (Format) and resource (SQL) and names several concrete dialects, which distinguishes it from the JSON/code formatters among siblings. It does not explicitly contrast with format_json or minify_code, but the SQL-specific framing is unambiguous.

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 second sentence only describes configurable options (keyword case, indent), not when to use this tool versus alternatives or any prerequisites. There is no when/when-not guidance; usage is merely implied by the tool's name.

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