get_query_suggestions

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

With no annotations provided, the description must disclose behavioral traits. It only mentions returning 'Suggested SQL queries' without addressing side effects, authentication needs, rate limits, or error handling. The read-only nature is implied but not explicitly stated.

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 concise with two sentences plus a structured Args/Returns section. Every sentence adds value, and the main purpose is front-loaded. The structure could be slightly tighter but is well-organized.

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 simplicity and presence of an output schema, the description covers the basic functionality and return type. However, it lacks details on prerequisites (e.g., database existence), potential errors, or how suggestions relate to the table structure. It is minimally 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?

The input schema has 0% description coverage, so the description compensates by defining both parameters: 'database_id: The ID of the database' and 'table_name: Name of the table'. While brief, these definitions add necessary semantic meaning beyond the schema's types.

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 verb 'Get' and the resource 'AI-suggested queries for a table based on its structure'. This distinguishes it from sibling tools like execute_query or explain_query, which operate on queries rather than suggest them.

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 the tool is for retrieving suggested queries, but it does not provide explicit guidance on when to use it versus alternatives like execute_query or get_table_metadata. No exclusions or when-not-to-use advice is given.

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