list_table_structure

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

No annotations provided, so description carries full burden. It discloses error behavior (table doesn't exist or has no columns), case-sensitivity, and that it does not accept GLOB patterns. It does not explicitly state read-only nature, but that is implied. Overall good transparency.

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?

Well-organized with clear sections: purpose, usage guidelines, parameter details, error handling. Every sentence adds value, though slightly verbose. Front-loaded main purpose.

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?

No output schema, but description specifies returned columns (name, type, nullability, primary-key flag). Covers error conditions and prerequisites. For a simple single-parameter tool, this is 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 coverage is 100% for the single parameter. The description adds meaning: explains that it accepts alias 'name' (v0.11.3+), is case-sensitive, requires exact match, and should match list_tables output. This goes well beyond the schema description.

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 states 'Show the columns of a table or view: name, type, nullability, primary-key flag.' This is a specific verb and resource, clearly distinguishing it from sibling tools like list_tables (lists tables) and execute_sql (runs 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?

Explicitly provides when to use ('writing or debugging a query — call this immediately after a `no such column` error') and when not to use ('don't write SELECT * FROM list_table_structure inside execute_sql'). Also advises to call list_tables first if uncertain about the table name.

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