analyze_data_viz

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

No annotations are provided, so the description must convey behavioral traits. It states the tool checks chart type appropriateness, color usage, labels, and accessibility, implying a read-only analysis without side effects. However, it does not disclose potential requirements (e.g., file format, permissions) or details about the analysis outcome, leaving some ambiguity.

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 communicates the tool's purpose and scope without any extraneous information. Every phrase ('Review data visualization for accessibility and clarity', 'Checks chart type appropriateness, color usage, labels, and accessibility') serves a clear purpose.

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?

For a straightforward analysis tool with three parameters and no output schema, the description adequately covers the tool's function and scope. However, it omits information about return values or confirmation of completion, which would enhance completeness. Overall, it is sufficient for the given complexity.

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 input schema already covers all three parameters with descriptions, achieving 100% coverage. The description adds no additional meaning beyond what the schema provides, such as formatting constraints or example values, resulting in minimal added value.

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 ('Review') and a clear resource ('data visualization'), and explicitly lists the aspects checked (chart type, color, labels, accessibility). It clearly distinguishes itself from sibling tools like 'check_contrast' or 'generate_accessibility_report' by focusing on the visualization as a whole.

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 lacks explicit guidance on when to use this tool versus alternatives such as 'analyze_accessibility' or 'review_usability'. It does not provide context for when not to use it or prerequisites, leaving the agent to infer usage solely from the vague scope.

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