Profile Table

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it does not state whether the tool is read-only, how expensive it could be, or how it handles empty/missing data. It lists outputs, but important behavioral traits like modification safety, performance, or error conditions are left unstated.

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?

A single, tightly worded sentence packs a clear purpose and the core delivered statistics. There is no fluff—every word adds signal: it says what, what what purpose, and what kind of output.

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 the high-level goal but does not explain the parameter semantics or usage boundaries, which matters because the schema descriptions are empty. Even though an output schema exists, the tool cannot be reliably invoked with just this description plus schema.

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 0%, so the description should compensate by explaining the three parameters. It only vaguely implies table_name via 'Profiles a table' and never explains columns or max_columns, including optionality, defaults, or effects. This is a critical gap for correct invocation.

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 specific function: profiling a table for visualization with row count and per-column statistics to guide chart selection. It distinguishes the tool from siblings like sample_table_data or get_table_schema by emphasizing the analytical/statistical output and visualization intent.

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?

It gives clear context: this is used to determine an appropriate chart by inspecting table characteristics. It does not explicitly name alternatives or when not to use it, so it stops short of a 5, but the intended use case is sufficiently communicated.

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