hot_partitions

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

With no annotations, the description must disclose behavioral traits. It states the tool lists partitions by file and record count, but does not mention sorting order, read-only nature, potential performance impact, or that limit applies to the top N records. This leaves significant behavioral ambiguity.

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 highly concise at 14 words and directly states the main purpose. However, it omits essential parameter details that could be included without much bloat, earning a slight deduction.

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 the output schema exists, return values do not need explanation. However, the description fails to cover basic parameter definitions, usage context, and behavioral details. For a two-parameter tool, this is inadequate.

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 has 0% parameter description coverage, and the description does not explain the 'table' (required) or 'limit' (default 20) parameters. The tool's purpose implies 'table' is needed, but no details on format or constraints are given, forcing reliance on schema 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 clearly states the tool lists the hottest Iceberg partitions by file count and record count to detect skew, specifying the verb ('list'), resource ('Iceberg partitions'), and criteria ('hottest by file count and record count'). It distinguishes itself from sibling tools like partition_pruning_check and get_table_health by focusing on partition skew 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 does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. For example, it does not clarify if this should be used after partition_pruning_check or in conjunction with get_table_health.

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