analyze_data_visualization

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

No annotations are provided, so the description must carry full burden. It discloses the core behavior (extract insights/trends) and accepted image formats in args, but does not discuss limitations, output structure, or potential failure modes. It is not misleading, so a moderate score is appropriate.

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 concise with a clear purpose sentence and structured Args list. No redundant information; every sentence adds value.

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?

With 2 parameters and an output schema, the description is adequate for selecting and invoking the tool. It lacks explicit alternative guidance but covers the essential context (chart types, optional question).

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 covers 0% of parameters, but the Args section in the description provides meaningful semantics: image supports path/URL/base64 URI, and question is an optional focus. This compensates well for the lack of schema 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 reads data visualization charts (bar/line/pie, dashboards) and extracts insights/trends, with a specific verb and resource. It distinguishes from siblings like image_analysis by targeting charts specifically.

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 implies usage for data visualization images with an optional focus question, but does not explicitly mention when not to use or alternatives like image_analysis or understand_technical_diagram. Clear context but no exclusions.

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