get_table_detail

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

With no annotations, the description carries the full burden. It states the return format (JSON with columns and ddl) but does not disclose whether the operation is read-only, has side effects, or requires authorization beyond registration. Adequate but not rich.

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 appropriately sized, front-loading the purpose in the first sentence. The argument list and return description are clear and concise, 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 presence of an output schema and 3 required parameters, the description covers the essential behavior. It does not mention prerequisites (e.g., instance must be registered) but that is implied by the parameter description. Sufficient for a read-oriented tool.

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 0%; the description lists all three parameters with brief context ('The instance name from register_instance'). This adds some meaning beyond the schema's type-only declarations, but lacks format details or constraints.

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 resource 'table detail' (column info and DDL). It distinguishes well from siblings like list_tables (which only lists names) and execute_sql (which runs arbitrary queries).

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 implicitly tells when to use this tool: when column info or CREATE TABLE DDL is needed. It does not explicitly exclude alternative tools, but the sibling names (list_tables, execute_sql) make the context clear.

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