analyze_table

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

No annotations are present, so the description carries the burden. It implies read-only behavior via 'quick statistical snapshot' and scoping to one table, but doesn't explicitly state whether the tool modifies data or requires specific permissions. The description adequately conveys the non-destructive nature and scope.

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 two sentences: the first states the core functionality with specific details, the second provides an alternative. It is front-loaded with 'QUICK statistical snapshot' and contains no superfluous words.

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 no output schema and no annotations, the description covers the main purpose, scope (one table), and available statistics. However, it does not mention output format or any prerequisites. It is adequately complete for a quick statistical 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?

The input schema is empty (no parameters), so schema coverage is 100%. The description adds value by detailing what the tool analyzes (row count, null rates, etc.), which is not in the schema. This fully compensates for the lack of parameters.

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 provides a 'QUICK statistical snapshot for ONE table' listing specific stats (row count, null rates, cardinality, numeric min/max/avg, date ranges). It also distinguishes itself from the sibling 'data_profile' by noting the alternative is for a 'FULL quality report including PII detection'.

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 explicitly says 'Use `data_profile` when the user wants a FULL quality report including PII detection,' providing clear guidance on when to use this tool vs. an alternative.

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