qlty_negativeValues

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

The description discloses the behavioral trait that setting persist=True materializes a volatile table and returns its name. However, with no annotations, it omits other important aspects like whether the tool modifies data, requires special permissions, or has rate limits.

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 exceptionally concise: three short sentences plus a bulleted argument list. Every sentence adds value, and the structure is efficient with no waste.

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 has a moderate complexity with 3 parameters but no output schema. The description fails to explain the return format (e.g., list of column names) except when persist=True (returns table name). For a data analysis tool, this leaves agents uncertain about what to expect.

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%, so baseline is 3. The description adds no additional meaning beyond what the schema already provides for each parameter. It merely repeats the parameter 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 returns 'column names that have negative values in a table,' which is a specific verb+resource. It distinguishes itself from sibling tools like qlty_columnSummary and qlty_missingValues by focusing on negative values.

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 provides no guidance on when to use this tool versus alternatives (e.g., qlty_missingValues for nulls) or when not to use it. No context or exclusions are mentioned.

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