get_data_quality_stats

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

With no annotations, the description bears full responsibility for behavioral disclosure. It fails to mention any traits such as caching, aggregation, query behavior, or potential side effects. The description only lists output metrics, omitting how or when the tool should be invoked.

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 sentence that efficiently conveys the purpose and returns. No filler or redundant information, making it highly concise and easy to parse.

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 zero-parameter input and lack of output schema, the description is fairly complete. It lists the specific metrics, which suffices for a simple retrieval tool. However, it could be enhanced with brief context on what 'data quality' encompasses, but overall it is adequate.

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 tool has zero parameters, so the schema provides no information. The description adds value by listing the specific metrics returned, which is useful beyond the empty schema. Per guidelines, 0 parameters yields a baseline of 4, and the description provides adequate, though minimal, semantic content.

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 it retrieves data quality metrics and lists specific metrics (translation coverage, embedding coverage, etc.), making the purpose unmistakable. It distinguishes itself from sibling stats tools like get_worker_stats or get_storage_stats by focusing on data quality rather than system or processing stats.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not indicate context, prerequisites, or scenarios where this tool is preferred over other stats tools, leaving the agent to infer without support.

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