drop_missing

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 explains the how and subset logic, but does not disclose whether the operation modifies the dataframe in-place or returns a new one, nor does it mention any effects on the current dataframe. It also omits the df_name parameter entirely. The core behavior is clear, but operational side effects are unaddressed.

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 three concise sentences plus a clear example. It front-loads the primary action, explains parameters efficiently, and provides a usage example. No fluff or redundant 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?

The tool is relatively simple, and an output schema exists to explain return values. However, the description omits the df_name parameter and does not clarify whether the operation is in-place or returns a new dataframe. Given the lack of annotations and 0% schema coverage, these gaps make the description only partially complete.

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%, so the description must compensate. It explains 'how' and 'subset' with defaults and examples, but the 'df_name' parameter is never mentioned. Two of three parameters are well-covered, but the missing df_name is a notable gap given the absence of schema descriptions.

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: 'Drop rows with missing values.' It further defines the two modes of operation (how and subset) and differentiates from fill_missing by specifying when to use each. This is a specific verb+resource description with clear scope.

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?

Explicit guidance is provided: 'Use when entire rows are invalid. For partial missingness, prefer fill_missing instead.' This directly tells the agent when to use this tool versus the sibling fill_missing tool. The example further clarifies usage.

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