qlty_missingValues

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

No annotations are present, so the description carries full burden. It explains the optional persist behavior and mentions that it returns column names. However, it lacks details on edge cases (e.g., empty table), return format, or side effects. The description is adequate but not rich in behavioral context.

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 concise with minimal sentences, each adding value: purpose statement followed by clear parameter explanations. There is no redundant or filler text. Front-loaded with purpose makes it immediately useful.

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 simple with 3 parameters and no output schema. The description covers the main behavior but does not specify the exact return format (e.g., list of strings vs. comma-separated). Given moderate complexity, it is minimally complete but could be improved with return type details.

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 100%, as each parameter has a description in the schema. The tool description repeats these descriptions without adding significant new meaning. Since the schema already documents the parameters, the description adds marginal value, meeting the baseline of 3.

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: 'Get the column names that have missing values in a table.' It uses specific verbs ('Get') and resources ('column names'), and distinguishes from siblings like 'qlty_rowsWithMissingValues' by specifying that it returns column names, not rows.

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 explicit when-to-use or when-not-to-use guidance relative to alternatives. The univariate nature of the tool is implied but not contrasted with other quality tools. There are no exclusions or context on prerequisites.

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