describe_table

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

With no annotations provided, the description carries the full burden of transparency. It explicitly enumerates what the tool returns (column names, data types, constraints, indexes) and the verb 'show' implies a non-destructive read operation. It does not discuss permissions or error behavior, but for a read-only metadata tool, this is adequate.

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 three concise sentences with no filler. The purpose is front-loaded, and the additional details about included items and intended usage are directly relevant, making every sentence earn its place.

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 description covers the tool's purpose, output contents, and intended usage context. The presence of an output schema and fully described parameters helps complete the picture. Minor gaps like permissions and error conditions are not critical for this simple read-only 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?

Both parameters (connection, table_name) are fully described in the input schema with 100% coverage. The tool description adds no additional parameter semantics beyond what the schema already provides, so a baseline score 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 ('Show') and clearly defines the resource ('full column definitions, types, constraints, and indexes for a table'). This distinguishes it from sibling tools like list_tables and get_sample_data, which serve different purposes.

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 provides clear context by stating 'The editor AI reads this to understand the exact schema before generating queries.' This implies when to use the tool, but it does not explicitly name alternatives or exclusion cases, so it falls short of a 5.

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