base_tableAffinity

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

Description adds behavioral context such as revealing natural JOIN relationships and data affinity patterns, and explains the persist parameter's effect of materializing a volatile table. Annotations already declare readOnlyHint and idempotentHint, so the description complements them without contradiction.

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 concise, front-loaded with the purpose, and includes usage guidelines and argument list in a clear structure. A small improvement could be organizing the argument list more formally.

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 covers purpose, usage, and parameters, but lacks details about the output format or example results. With no output schema, more descriptive output would enhance completeness.

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 description coverage is 100%, so the baseline is 3. The description repeats parameter names and purpose but adds no additional meaning beyond what the schema already provides.

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 identifies co-occurring tables in SQL queries, revealing JOIN relationships and affinity patterns. It uses a specific verb 'Identify' and distinguishes from sibling tool base_tableUsage.

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 states when to use (queries about tables queried together, related tables, common workflows) and when not to (access frequency, query counts, per-user stats), directing to base_tableUsage as alternative.

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