describe_table

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

With no annotations, the description carries full burden. It discloses the authorization constraint (allowlisted) and the scope of returned info (columns exposed by policy, types, etc.). Does not mention side effects or errors, which are minor given the read-only nature implied by 'describe'.

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?

Single sentence, front-loaded with the action, and efficiently lists all return aspects. No redundant words; every piece earns 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?

Given the simple tool (1 param, no output schema), the description is nearly complete. It covers purpose, input constraint, and output content. Minor gap: no mention of error handling for nonexistent tables, but this is acceptable for a straightforward describe 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 coverage is 100%, so baseline is 3. The description adds value by reinforcing that the table must be allowlisted and by providing a concrete example ('public.orders'), which aids correct parameter usage.

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 specific verb 'describe' and resource 'one allowlisted table', listing exactly what metadata is returned (columns, types, nullability, keys, indexes). It clearly distinguishes from siblings like list_tables (listing tables) and run_query (executing SQL).

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 indicates use for table schema inspection, but lacks explicit guidance on when not to use or alternatives. However, the context of sibling tools and the specific language about allowlisted tables provides sufficient contextual clarity.

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