detect_missing_values

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

With no annotations provided, the description carries the full burden. It does explain the output behavior (counts, percentages, sorting by most-missing), which is useful. However, it does not disclose any side effects, limitations, or assumptions (e.g., whether all columns are included, handling of empty files), leaving some behavioral aspects unexplored.

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 a single, concise sentence that starts with the action verb 'Report' and includes the key details (counts, percentages, sorting). Every word earns its place, and there is no fluff or redundancy.

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?

For a simple one-parameter tool with an output schema, the description provides sufficient information about what it does and what it returns. It is reasonably complete despite the lack of parameter explanation, because the parameter is self-evident from the context. Slightly higher than mid-tier because the output behavior is clearly specified.

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 has one required parameter 'filename' with 0% description coverage, and the tool description does not mention it at all. While the parameter's purpose is inferable from the tool name, the description does not add any extra meaning, such as accepted file formats or how the filename is used, which is a gap given the low schema coverage.

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: 'Report missing-value counts and percentages per column, sorted by the most-missing first.' This is a specific verb ('report') with a clear resource (missing-value stats per column) and unique sorting behavior, distinguishing it from sibling tools like profile_dataset or plot_distribution.

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 implies when to use the tool (when you need missing-value insights per column) but does not explicitly mention when not to use it or suggest alternatives. There is no comparison to sibling tools, so usage guidance is inferred rather than explicit.

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