describe_column

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

The readOnlyHint annotation already establishes the safe read-only nature. The description adds valuable behavioral context by disclosing caps on top_n and histogram_bins, and clueing the user into the type of output (distribution, histograms, temporal range). It does not contradict the annotation.

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 (three sentences) and front-loaded with the core purpose. Each sentence carries useful information: output types, column type handling, and caps. No unnecessary 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?

With no output schema, the description does a good job explaining the return shape (distribution, histogram, temporal range) and constraints. It could mention sample output or redaction behavior, but the schema covers those. Overall, it is sufficient for a 6-parameter tool with a clear purpose.

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 schema already has 100% coverage for parameter descriptions. The description adds meaning beyond the schema by specifying maximum caps (top_n <= 200, histogram_bins <= 50), which are not present in the schema's default-based descriptions. It also clarifies how histogram_bins applies to numeric data.

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's purpose with a specific verb ('Deep profile') and resource ('single column'), distinguishing it from dataset-level tools like describe_dataset. It also specifies the types of profiling (value distribution, histogram bins, temporal range), making its function unambiguous.

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 does not provide explicit guidance on when to use this tool versus alternatives like get_distribution or get_data_hotspots. It implies a 'deep profile' use case but lacks clear context, exclusions, or alternatives.

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