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

No annotations are provided, so the description carries the full burden. It mentions that it returns a .sql file with comments, but it doesn't disclose edge cases, limitations (e.g., complexity of queries, dialect support), or what happens if the request is ambiguous or the schema is incomplete.

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 one concise sentence that front-loads the purpose and output. It's efficient with no wasted words.

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 the tool's complexity (SQL generation) and the lack of annotations and output schema, the description is somewhat minimal. It doesn't explain how the dialect parameter works, what inputs are expected (e.g., schema format), or any limitations. For a tool with this complexity, more detail would be beneficial.

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 schema has 3 parameters (schema, dialect, request) but 0% description coverage. The description mentions 'table schema' and 'plain-language request', which loosely maps to 'schema' and 'request', but it doesn't explain the 'dialect' parameter or what values it accepts. The description adds minimal value over 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?

The description clearly states the tool takes a plain-language request and table schema to produce a ready-to-run .sql file with comments. It distinguishes from siblings like transpile_sql (which converts between SQL dialects) and regex_test, but it doesn't explicitly name alternatives.

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?

It implies the use case of generating SQL from natural language and schema, but it doesn't provide explicit when-to-use or when-not-to-use guidance or mention alternatives like transpile_sql for converting SQL. The distinction from siblings is minimal.

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