auto_quality

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

No annotations are provided, so the description carries the full burden. It does not disclose whether the tool is read-only, what the output looks like, any side effects, or what 'safe and clean' concretely evaluates. While it implies an audit/check operation, it lacks behavioral detail.

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, front-loaded sentence that immediately conveys the tool's purpose and scope. Every word earns its place, with no filler 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?

Given the tool has an output schema (not shown here), return values may be covered by that. However, the description lacks contextual detail about the process, prerequisites, or limitations. For a tool combining multiple checks, it is minimally adequate but could benefit from mentioning that it aggregates standard checks into a report.

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 coverage is 0%, and the description does not explicitly explain the 'source_id' parameter. The name is self-explanatory to an extent, and the description refers to 'data' which hints at the source, but it adds no semantic detail beyond the schema's basic type and name.

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 covers quality, duplicates, PII, and bias in one call. This gives a specific verb (checks/evaluates) and resource (data quality dimensions), and distinguishes it from sibling tools like check_duplicates, check_pii, and check_bias by combining them.

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 phrase 'in one call' implies this is a comprehensive alternative to running individual check tools separately. It provides clear context for when to use it (when a quick multi-faceted quality assessment is needed), though it does not explicitly name alternatives or exclusions.

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