pivot_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. It only says 'pivot table in Excel style' and reveals nothing about whether this reads data, creates a new artifact, aggregates values, or has side effects. The description adds no behavioral information beyond the tool's name.

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 single phrase is very short and front-loaded, with no filler words. However, it is under-specified rather than efficiently complete, and the lack of structure means the agent gets no semantic organization to help with invocation. Conciseness is achieved at the expense of necessary information.

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?

This is a five-parameter tool with no annotations, no parameter-level description coverage, and a one-line generic description. The output schema exists, but the description still fails to explain the operation's inputs, expected behavior, or relationship to sibling tools. The definition is far from complete enough for reliable agent invocation.

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 0%, and the description provides no clarification for any parameter. The five parameters (table_name, row_columns, col_column, value_column, agg_function) remain entirely unexplained, so an agent must guess their meaning and constraints from names alone.

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 identifies the concept ('Сводная таблица в стиле Excel (PIVOT)') and implies a pivot-table operation on a table, so an agent can roughly infer purpose. However, it lacks a specific verb and does not differentiate from sibling tools like cross_tab, which likely overlap heavily. The name itself does most of the work.

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?

There is no guidance on when to use this tool versus alternatives. The sibling list includes cross_tab and sql_query, which could serve similar analytical purposes, but the description gives no selection criteria or exclusions. Usage context is entirely absent.

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