im_describe_table

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

No annotations are provided, so the description carries the full burden. It indicates a read-only operation showing schema details, but does not disclose potential side effects (none expected), permissions needs, or response format. 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?

Two sentences, front-loaded with the action, no redundant words, clearly structured. Every sentence provides value.

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?

For a simple tool with one parameter, no annotations, and no output schema, the description is sufficiently complete. It tells what the tool does and when to use it. Could mention that the output is a table-like result or that it is safe to call repeatedly.

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% with description for table_name including example usage. The tool description adds no additional meaning beyond the schema; it restates the purpose. Baseline 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 explicitly states the tool shows column names, data types, nullability, and default values for a given table, and adds context about helping understand table structure before writing queries. This clearly distinguishes it from sibling tools like im_list_tables (lists tables) and im_execute_select (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?

The description implies use when understanding table structure before writing queries ('Helps understand IntelliMatch table structure before writing queries'), but does not explicitly state when to avoid the tool or mention alternative tools for similar tasks. No explicit guidance on prerequisites or exclusions.

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