suggest_visualizations

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

No annotations exist; description does not disclose behavioral traits such as being read-only, requiring data to be loaded, or any side effects. The description is too generic.

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?

Single sentence that is front-loaded and concise. Every word adds value without 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?

With one required parameter and an output schema (existence indicated), the description is adequate but vague. It does not specify what visualization types might be suggested or constraints.

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 is 100% with one parameter 'dataset_name'. The description adds 'based on data characteristics' but provides minimal additional meaning beyond the schema.

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's verb ('suggest') and resource ('visualization types') and adds context ('based on data characteristics'), distinguishing it from siblings like 'create_plot' or 'analyze_data'.

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 on when to use this tool vs. alternatives like 'analyze_data' or 'create_plot'. Lacks when-not-to-use or prerequisite conditions.

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