data_quality_report

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

With no annotations provided, the description carries the full behavioral disclosure burden. It does state 'Read-only', which is valuable safety-relevant information, but it does not mention details such as performance expectations, required permissions, or behavior with empty or large datasets. It adds some transparency beyond the schema but is not comprehensive.

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 with no filler. It states the action, the target, the output contents, and the safety profile efficiently. Every word earns its place.

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 simple interface and an output schema, so the description covers the main purpose and read-only nature. However, it lacks usage guidance and does not clarify the optional columns parameter, leaving part of the call semantics underspecified. This is adequate for a basic invocation but incomplete for confident optional-parameter usage.

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 0%, so the description must compensate, but it only mentions 'per-column' and does not explain the optional 'columns' parameter or how it affects the report. The names file_path and sheet_name are self-explanatory, but the semantics of the optional columns list (filtering vs inclusion) remain ambiguous. The description fails to add meaning beyond the parameter names.

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 uses a specific verb ('Produce') and clearly identifies the resource ('data quality report for a workbook sheet') plus the report contents ('per-column type, completeness, uniqueness and numeric stats'). It is clear and actionable, though it does not explicitly distinguish itself from sibling tools such as summary_statistics or read_excel_metadata.

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?

There is no guidance on when to use this tool versus alternatives like summary_statistics, validate_workbook, or read_excel_metadata. The description implies a read-only exploratory use case but does not state conditions, exclusions, or preferred tool selection.

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