describe_table

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

No annotations are provided, so the description must bear the entire burden of disclosing behavioral traits. It does not mention whether the operation is read-only, whether it can fail on non-existent tables, or any side effects. While the tool name and wording imply a harmless read, the description offers no explicit transparency about error handling or assumptions, leaving an agent potentially uninformed.

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 a single, direct sentence that immediately communicates the core function and output fields. There is no filler or redundancy, and it is appropriately sized for a one-parameter utility tool.

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 the simplicity of the tool, the description covers the essential information: it states the input (table) and the output (column details). It lacks explicit notes on error cases or prerequisites, but for a straightforward metadata query, this is largely sufficient. The existence of an output schema reduces the need to describe return values in detail.

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 provides only a parameter name 'table' with type string, and schema description coverage is 0%. The description adds the semantic that the parameter refers to the table whose columns are to be described, which is valuable. However, it does not specify format constraints (e.g., whether it must match an existing table exactly, case sensitivity, or quoting rules). It partially compensates for the schema gap but could be more explicit.

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 a specific verb (describe) and resource (table columns), and clearly specifies the returned attributes: name, type, and required status. This distinguishes it from sibling tools like list_tables (which lists table names) and run_query (which executes queries). An agent can accurately select this tool for schema inspection without ambiguity.

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 should be used when needing column-level metadata for a specific table, but it does not explicitly state when to prefer it over alternatives or mention exclusions. For example, it does not say 'use run_query for filtering data' or 'use list_tables to see available tables.' The context is clear from the purpose, but explicit routing guidance is missing.

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