base_tableAffinity

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 mentions the 'persist' parameter materializing results but fails to disclose whether the tool is read-only, permissions required, rate limits, or behavioral traits like destructive actions. The description is insufficient for safe agent invocation.

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 relatively concise with two sentences and a parameter list. However, the parameter list is redundant with the input schema, which slightly detracts from conciseness.

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 lacks an explanation of what the tool returns (e.g., list of table names, scores, or results format). The 'persist' parameter mentions returning a table name, but the overall output is unclear. For a tool with no output schema, this gap is notable.

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?

Input schema has 100% description coverage, and the description's parameter list essentially repeats the schema descriptions, adding no new meaning. Baseline score is appropriate as the schema already documents parameters adequately.

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 clearly states the tool retrieves tables commonly used together by database users, aiding in inferring relationships between tables. The verb 'Get' is specific and the resource 'tables commonly used together' is distinct from siblings like base_tableUsage or graph tools.

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 usage for relationship inference but does not provide explicit when-to-use or when-not-to-use guidance, nor does it name alternative tools. The context is implied but lacks direct instructions.

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